50+ Machine Learning (ML) Jobs in India

About GeniWay

GeniWay Technologies is building AI-powered products that help students learn effectively and make confident education and career decisions.

Our first product, Clario, combines multidimensional student assessment, career intelligence, personalized guidance, and AI-assisted counselling for Indian students and families.

With Clario’s initial platform nearing completion, our next major ambition is to build an AI-powered personalized learning platform that adapts learning experiences to each student’s knowledge, goals, learning patterns, motivation, and progress.

We are looking for an AI-native engineering leader to help turn this ambition into a trusted, scalable product.

The Opportunity

We are hiring a Founding AI Engineering Lead, CTO Track to become GeniWay’s full-time technical operating leader.

Your primary mandate will be to lead the engineering of our AI-powered personalized learning platform. You will also own the continued evolution, reliability, and scale-readiness of Clario.

This is not a conventional engineering management role or a role limited to integrating third-party AI APIs. It requires someone who can combine:

• deep applied-AI expertise;
• strong product and architectural judgment;
• hands-on full-stack engineering;
• engineering-team leadership; and
• responsible deployment of AI for students.

For an exceptional leader who demonstrates sustained company-level technology leadership, this role offers a credible pathway toward becoming GeniWay’s future CTO.

What You Will Build

The personalized learning platform is expected to progressively support:

• continuously evolving learner profiles;
• personalized learning pathways and interventions;
• adaptive content, practice, and assessments;
• AI tutors, mentors, and learning companions;
• multi-agent workflows for learning support and content operations;
• student progress, mastery, and engagement intelligence;
• evidence-grounded recommendations for students, parents, and educators;
• responsible human oversight, safety, and explainability.

You will help define the architecture, technical strategy, and delivery roadmap required to build these capabilities responsibly.

What You Will Own

AI Product and Platform Engineering

• Own the architecture and engineering of GeniWay’s personalized learning platform.
• Translate learning-product concepts into reliable AI-powered experiences.
• Design and build GenAI, agentic-AI, and ML-enabled workflows.
• Determine when to use LLMs, deterministic logic, retrieval, conventional ML, or human review.
• Build reusable AI-platform capabilities instead of isolated prompt-based features.
• Lead experimentation, evaluation, production deployment, and continuous improvement of AI capabilities.

Applied AI Quality and Safety

• Establish evaluation frameworks for accuracy, relevance, personalization, consistency, latency, and cost.
• Design safeguards against hallucinations, unsafe guidance, bias, prompt injection, and inappropriate student interactions.
• Build observability and feedback loops for AI behaviour in production.
• Ensure student-facing AI systems are explainable, privacy-conscious, age-appropriate, and human-supervised where required.
• Work with product and domain specialists to validate educational usefulness, not merely technical performance.

Product Engineering and Delivery

• Own end-to-end engineering delivery across AI, backend, frontend, data, and infrastructure.
• Lead or personally implement critical product capabilities when required.
• Establish predictable planning, development, testing, release, and incident-management practices.
• Scale and strengthen Clario while building the next product platform.
• Balance speed, product quality, maintainability, scalability, and operating cost.

Architecture and Data Foundations

• Define and evolve the application, AI, data, and cloud architecture.
• Build secure foundations for learner profiles, content intelligence, personalization, and analytics.
• Establish effective data pipelines, model interfaces, APIs, and platform services.
• Make pragmatic build-versus-buy and model-selection decisions.
• Reduce technical debt and material technology risks systematically.

Team and Technology Leadership

• Lead, mentor, and raise the effectiveness of the engineering team.
• Build strong AI and software-engineering practices across the organization.
• Help recruit future AI, data, and product engineers.
• Work closely with the Founder on product strategy, priorities, and technology investments.
• Develop GeniWay’s longer-term technology strategy and engineering organization.

Essential Capabilities

• Strong hands-on experience building and operating AI-powered products in production.
• Deep practical understanding of GenAI application architecture, LLM behaviour, prompting, context engineering, and structured outputs.
• Experience building agentic or multi-step AI workflows with appropriate controls and observability.
• Experience with retrieval-augmented generation, embeddings, semantic search, or knowledge systems.
• Ability to evaluate AI quality systematically rather than relying on subjective demonstrations.
• Strong Python, backend, API, database, and system-design capabilities.
• Ability to lead full-stack product engineering beyond the AI layer.
• Experience leading engineers and owning complex product delivery.
• Strong product judgment and ability to translate ambiguous goals into executable plans.
• High ownership, urgency, reliability, and transparent communication.

Strongly Preferred

• Experience building personalization, recommendation, adaptive-learning, tutoring, or conversational-AI products.
• Practical AI/ML experience involving experimentation, feature engineering, model evaluation, or predictive systems.
• Experience with LLMOps or MLOps, including evaluation, monitoring, versioning, and deployment.
• Experience designing AI guardrails and responsible student-facing systems.
• Experience as a founding engineer, technical lead, or early engineering leader.
• Experience building AI-native products from zero to one.
• Interest in learning science, education, and student outcomes.

What We Are Not Looking For

• A pure people manager who is no longer technically hands-on.
• A research-only AI specialist without strong product-engineering capability.
• Someone whose GenAI experience is limited to basic chatbot or API integrations.
• A generalist engineering leader with little evidence of applied-AI delivery.
• An advisor seeking influence without full-time operating accountability.

What Success Looks Like

First 90 Days

• Take operational ownership of GeniWay’s engineering function.
• Understand and strengthen Clario’s architecture, quality, and scale-readiness.
• Define the technical architecture and phased roadmap for the personalized learning platform.
• Establish AI evaluation, safety, engineering-quality, and release practices.
• Improve team accountability, execution rhythm, and delivery predictability.

First 6-9 Months

• Deliver the first meaningful version of the personalized learning platform.
• Establish reusable foundations for learner modelling, personalization, AI agents, evaluation, and observability.
• Demonstrate measurable educational and product value from AI capabilities.
• Build a dependable engineering and AI delivery organization.
• Demonstrate readiness for broader CTO-level responsibility.

Compensation and Growth

• Fixed compensation: ₹20L–₹25L per annum, based on capability and experience
• Performance-linked variable: Up to 15%–20%, tied to agreed outcomes
• Initial ESOP grant: Approximately 0.75%–1.25%, based on fit and expected ownership
• Leadership equity top-up: Potential additional 0.5%–1% after 12–18 months, based on sustained contribution and evolution toward CTO-level responsibility
• Leadership review: Formal assessment after six months, followed by a broader role and compensation review after 12 months

The CTO pathway is earned through demonstrated technology strategy, AI-product leadership, organizational impact, and company-level ownership.

Selected candidates will complete structured discussions covering applied-AI depth, architecture, hands-on engineering, product judgment, responsible AI, leadership approach, and long-term alignment.

Job Description: AI/ML Engineer

Location: Gurgaon, Haryana, India

Position: AI/ML Engineer -Intern

Stipend: As per industry standards

About Aaizel Tech

Aaizel Tech is a pioneering tech startup at the intersection of cybersecurity, AI, geospatial solutions, and more. We drive innovation by delivering transformative technology solutions across industries. As part of our dynamic team, you'll gain hands-on experience and learn from experts who are dedicated to pushing the boundaries of what's possible.

Key Responsibilities:

1. Model Development and Optimization:

• Design, implement, and deploy ML models for diverse applications, including predictive analytics, anomaly detection, and computer vision, tailored for cybersecurity, climate monitoring, and geospatial data analysis.
• Utilize deep learning (CNNs, RNNs), reinforcement learning, and generative models (GANs) for complex problem-solving.

1. Advanced Data Engineering:

• Develop ETL pipelines and preprocessing scripts using Pandas, Numpy, and PySpark to handle large datasets from satellite imagery, IoT sensors, and real-time data sources.
• Integrate data from APIs, databases, and big data platforms (Hadoop, Apache Kafka) to support real-time analytics.

1. Algorithm Research and Development:

• Research state-of-the-art ML techniques, including Transfer Learning, Transformer models, and AutoML, to enhance model performance.
• Innovate new algorithms for geospatial analysis, such as object detection on aerial imagery, spatial clustering, and environmental modeling.

1. Deployment and MLOps:

• Deploy models using Docker, Kubernetes, and CI/CD pipelines, ensuring robust model lifecycle management.
• Work with cloud platforms (AWS, Azure, GCP) to implement scalable model serving solutions, using technologies like Sage Maker, TensorFlow Serving, and ONNX.

1. Performance Evaluation and Tuning:

• Perform model evaluation using advanced metrics (F1 Score, AUC-ROC, Intersection over Union for spatial data) and optimize for both accuracy and inference speed.
• Implement hyperparameter tuning using Bayesian Optimization, Grid Search, and Neural Architecture Search.

6. Performance Evaluation and Tuning:

• Perform model evaluation using advanced metrics (F1 Score, AUC-ROC, Intersection over Union for spatial data) and optimise for both accuracy and inference speed.
• Implement hyperparameter tuning using Bayesian Optimization, Grid Search, and Neural Architecture Search.

1.      7. Collaboration and Code Quality:

• Collaborate with data engineers, cybersecurity experts, and geospatial analysts to integrate ML solutions into end-to-end products.
• Adhere to coding standards, participate in code reviews, and maintain high-quality codebases using Git, Jira, and Confluence.

     8.Monitoring and Maintenance:

• Develop monitoring dashboards using Grafana, Prometheus, or similar tools to track model performance post-deployment.
• Implement feedback loops for model retraining based on real-time data and evolving application needs.

Required Skills, Qualification and Experience:

Educational Background: Bachelor’s/Master’s in Computer Science, Data Science, Machine Learning, or a related field from preferably top-tier       institutions.

• Technical Proficiency:
• Strong skills in Python, PyTorch, TensorFlow, and Scikit-learn.
• Proficiency in SQL, NoSQL databases (MongoDB, Cassandra), and data warehousing solutions (Redshift, BigQuery).
• Problem-Solving: Analytical mindset with the ability to solve complex problems using data-driven approaches.
• Communication: Capable of translating technical details into actionable insights for diverse stakeholders.
• Adaptability: Ability to thrive in a high-paced, dynamic startup environment with a focus on rapid iteration and delivery.

About the Internship

Nexora Group is looking for passionate and innovative students interested in Artificial Intelligence (AI) and Machine Learning (ML). This internship offers an opportunity to work on real-world AI projects, explore machine learning techniques, and gain hands-on experience with emerging technologies that are transforming industries worldwide.

Interns will collaborate with mentors, work on practical assignments, and develop industry-relevant skills in AI, ML, data-driven decision-making, and intelligent systems.

Key Responsibilities

• Assist in developing and testing Machine Learning models.
• Work on AI-based applications and automation projects.
• Analyze datasets and prepare data for model training.
• Research emerging AI and Machine Learning technologies.
• Evaluate model performance and improve accuracy.
• Create reports and documentation for assigned projects.
• Participate in project discussions, training sessions, and team meetings.
• Support the development of innovative AI-driven solutions.

Required Skills

• Basic knowledge of Python programming.
• Understanding of Artificial Intelligence and Machine Learning concepts.
• Familiarity with data analysis and statistics.
• Knowledge of Machine Learning libraries such as Scikit-learn, TensorFlow, or PyTorch is a plus.
• Strong analytical and problem-solving skills.
• Ability to learn new technologies quickly.
• Good communication and teamwork skills.

Eligibility

• B.Tech, M.Tech, BCA, MCA, B.Sc., M.Sc., or related disciplines.
• Students pursuing Computer Science, Artificial Intelligence, Data Science, Information Technology, Mathematics, or related fields.
• Freshers and recent graduates are encouraged to apply.

What You Will Learn

✅ Artificial Intelligence Fundamentals

✅ Machine Learning Algorithms

✅ Data Preprocessing & Model Training

✅ Generative AI Concepts

✅ Predictive Analytics

✅ AI Project Development

✅ Industry-Oriented Problem Solving

Benefits

✅ Internship Completion Certificate

✅ Letter of Recommendation (Performance-Based)

✅ Hands-on AI & ML Project Experience

✅ Professional Mentorship & Guidance

✅ Resume & LinkedIn Profile Enhancement

✅ Portfolio Development Support

✅ Exposure to Real-World AI Applications

Job Title: Engineering Manager

Location- Delhi

Job type: Full time, On site

About Us: TIMBLE is leading Authentication Company, delivering cutting edge technology and alternate data analysis for Identity management, Onboarding & Verification and Business Intelligence. We provide solutions across three verticals

1. BFSI Solutions

2. KYC and background check Solutions

3.AI Solutions

Role Overview

As an Engineering Manager at Timble AI, you will manage, mentor, and scale our core engineering teams (including Backend, Frontend, and AI/ML divisions). You will remain highly technical, contributing to architecture decisions and system design, while taking full ownership of project delivery timelines, agile sprints, and team performance metrics.

Key Responsibilities

1. People Leadership & Mentorship: Manage and grow a cross-functional team of software engineers (SDE-1 to SDE-3). Conduct regular 1-on-1s, drive career growth paths, and foster an innovative, high-ownership engineering culture.
2. Delivery & Agile Project Management: Own the engineering sprint cycles. Work closely with Product Managers to break down roadmaps into execution goals, manage dependencies, and ensure high-velocity, predictable delivery.
3. System Design & Architecture: Provide technical governance and direction. Collaborate on core system architecture, design reviews, and ensure codebases remain clean, scalable, and modular.
4.  Engineering Excellence: Define and monitor key performance indicators (KPIs) for the engineering team, including code quality, test coverage, uptime, and system performance.
5. Hiring & Scaling: Actively partner with the talent acquisition team to identify, interview, and onboard top-tier engineering talent to help build our core verticals.

Required Skills & Qualifications

1. Experience: 5+ years of core software engineering experience, with at least 1–2 years of experience in an engineering management, tech lead, or team leadership role.
2. Technical Roots: Strong foundational background in backend systems, distributed architectures, or AI integration. Prior hands-on experience with Python/Django ecosystems, microservices, cloud infra (AWS/GCP), or heavy automation systems is highly valued.
3. Agile Mastery: Deep familiarity with Agile/Scrum development methodologies, sprint planning tools, and CI/CD pipelines.
4.  Communication: Exceptional interpersonal and cross-functional communication skills, with a track record of translating complex technical visions into clear execution steps.
5.  Education: B.Tech / M.Tech in Computer Science, Information Technology, or a related technical discipline from a reputed institute.

Learn more about us at: https://timbleglance.com

Job Title: Technical AI Product Manager (Agentic AI)

Location- Delhi

Job type: Full time, On site

About Us: TIMBLE is leading Authentication Company, delivering cutting edge technology and alternate data analysis for Identity management, Onboarding & Verification and Business Intelligence. We provide solutions across three verticals

1. BFSI Solutions

2. KYC and background check Solutions

3.AI Solutions

Key Responsibilities

1. Product Strategy & Roadmap: Own the end-to-end product lifecycle for AI-native and agentic products. Translate complex operational problems into AI-driven workflows and autonomous agent solutions.
2. Agentic AI Architecture: Prototyping multi-agent workflows using LangGraph, LangChain, and modern LLM tooling. Build systems featuring tool calling, structured memory, planning, and reflection capabilities.
3. Hands-on Development: Develop proof-of-concepts (PoCs) and MVPs using Python. Integrate LLM APIs, vector databases, retrieval systems, and custom prompt engineering techniques.
4.  Agile Execution: Convert stakeholder requirements into technical specifications, user stories, and high-quality PRDs. Lead sprint planning and agile ceremonies with backend and AI/ML teams.
5.  Performance & Metrics: Define and monitor AI-specific KPIs, including token latency, system reliability, contextual accuracy, and hallucination rates.

Required Skills & Qualifications

1. Experience: 4+ Years in Product Management or Technical Product Management (TPM).
2. Domain Expertise: Proven track record of shipping AI/ML, Generative AI, or LLM-based applications.
3. Technical Skills: Hands-on experience prototyping or designing AI agents/workflows. Strong programming literacy in Python to interface with data science frameworks.
4. Education: B.Tech/M.Tech in Computer Science or a related technical discipline from a reputed institute.

What We Offer

1.  Absolute ownership of the core agentic roadmap in a high-growth AI startup.
2. A collaborative, high-velocity workspace with zero corporate bureaucracy.
3. Competitive compensation packages and performance-driven trajectory.

Learn more about us at: https://timbleglance.com

Job Title: Product Lead or Tech Lead (AI & Infrastructure)

Location- Delhi

Job type: Full time, On site

About Us: TIMBLE is leading Authentication Company, delivering cutting edge technology and alternate data analysis for Identity management, Onboarding & Verification and Business Intelligence. We provide solutions across three verticals

1. BFSI Solutions

2. KYC and background check Solutions

3. AI Solutions

Role Overview-You will be the architectural backbone of Timble’s AI engine. This role requires a strong backend & systems mindset with exposure to AI/ML systems—balancing the development of high-accuracy fraud detection models with the scalable infrastructure required to run them.

Key Responsibilities

·      Engineering Leadership: Lead the development of our core AI products, including Bank Statement Analyzers, Face Match technology, and Electronic Residence Physical Verification (ERPV).

·      AI/ML Architecture: Design and deploy AI/ML-driven systems for document intelligence, fraud detection, and automation to enhance real-time intelligence.

·      Delivery Ownership: Take end-to-end ownership of features and ensure timely delivery in high-stakes production environments.

·      System Design & Scalability: Design and optimize high-throughput, low-latency API systems capable of handling real-world production loads across our 30+ high-quality APIs.

·      Hands-on Contribution: Remain hands-on with code when required, especially for critical modules, core architecture decisions, and troubleshooting.

·      Practical AI Application: Work on integrating and scaling AI/ML components in production. You must have the ability to apply complex AI solutions to solve real-world business problems.

·      Technical Strategy & InfoSec: Oversee Information Security protocols to protect proprietary financial data. Lead IP-related technical work, including patent-pending research for our authentication engines.

·      Mentorship: Act as the technical North Star for SDE-1 and SDE-2 engineers, instilling a culture of clean code, scalability, and cloud economics.

What We’re Looking For

·      Technical Expertise: Strong backend engineering expertise (Python or similar), with experience in building and maintaining scalable systems. Exposure to ML frameworks (TensorFlow/PyTorch) is a plus.

·      Domain Knowledge: Previous experience in Fintech, Cybersecurity, or BFSI tech stacks is highly preferred.

·      Infrastructure Skills: Solid experience with cloud infrastructure (AWS/GCP/Azure) and maintaining high availability.

·      Vision: The ability to translate complex fraud patterns into automated, executable code and a passion for "efficiency by design."

Learn more about us at: https://timbleglance.com

Description:

-> Work on full-stack development projects, handling both front-end and back-end development tasks.

-> Gain practical experience in designing, developing and deploying scalable web and application solutions.

-> Collaborate with teams to build efficient, secure, and user-friendly applications using modern technologies.

-> Work with a wide range of technologies and domains, including:

  Java Application Programming

  Web Development

  Python Application Programming with Django

  Machine Learning

  Data Science

  Artificial Intelligence

  Cyber Security

  Data Analytics

-> Develop problem-solving, analytical, and technical skills by working on projects.

Duration: 1 - 6 months

Mode: Online/Offline

Eligibility: Any BCA/MCA pursuing Students can apply.

Perks:

-> Internship Certificate

-> Letter of Recommendation.

Description:

-> Work on full-stack development projects, handling both front-end and back-end development tasks.

-> Gain practical experience in designing, developing and deploying scalable web and application solutions.

-> Collaborate with teams to build efficient, secure, and user-friendly applications using modern technologies.

-> Work with a wide range of technologies and domains, including:

  Java Application Programming

  Web Development

  Python Application Programming with Django

  Machine Learning

  Data Science

  Artificial Intelligence

  Cyber Security

  Data Analytics

-> Develop problem-solving, analytical, and technical skills by working on projects.

Duration: 1 - 6 months

Mode: Online/Offline

Eligibility: Any BE/BTech pursuing Students can apply.

Perks:

-> Internship Certificate

-> Letter of Recommendation.

Hi All,

Hope you are doing well,

If you are interested, please do revert back with the updated resume.

Position: Gen AI architect

Location: PAN India

Job Description:

AI/ML, Python, GenAI, Azure/AWS

Interview process:

1st level Assessment – HACKERRANK TEST(Candidate should be comfortable)

ML Engineer — Test & Learn Platform (3+ Years Experience)

About the Role

We're looking for an ML Engineer to join our Test & Learn Platform team. You'll build

and scale our experimentation and causal inference services — from statistical engines

to API integrations and cloud pipelines — empowering business teams globally to make

data-driven decisions.

What You'll Do

 Develop and maintain statistical/ML modules (DID, Synthetic Control, A/B

Testing, Multi-Treatment Effects) in Python

 Build and extend FastAPI services and integrate them with our web application

via SDK wrappers

 Design and optimize large-scale data pipelines using PySpark, Delta Lake, and

Azure Data Lake

 Profile and resolve OOM issues in PySpark jobs — optimize memory allocation,

partitioning, broadcast joins, caching strategies, and Spark configurations

 Deploy and manage workloads on Databricks, including job clusters, notebooks,

and Delta Lake tables

 Containerize and deploy services using Docker, Kubernetes, and CI/CD pipelines

 Ensure code quality and security via SonarCloud, Snyk, and pytest

 Collaborate with data scientists and product teams to translate research into

production-ready modules

Must-Have Skills

 Python (3.9+) — 3+ years of production experience

 PySpark & Spark Internals — strong experience with Spark memory model,

executor tuning, shuffle optimization, and diagnosing/resolving OOM errors

(broadcast thresholds, partition skew, spill-to-disk, GC tuning)

 Databricks — hands-on with job orchestration, cluster configuration, notebook

workflows, and Delta Lake optimization (Z-ordering, compaction, caching)

 Causal Inference & Experimentation — DID, synthetic control, A/B testing,

hypothesis testing, panel data methods

 Statistics/ML Libraries — statsmodels, scikit-learn, scipy, pandas, numpy

 API Development — building RESTful services with FastAPI (or similar)

 Cloud (Azure) — Azure Storage, Azure ML, Data Lake

 Docker & Kubernetes — containerization and orchestration for ML workloads

 Testing — writing robust unit/integration tests with pytest

Nice-to-Have

 Experience with Celery/Redis for async task orchestration

 Familiarity with Polars, PyArrow, or SQLAlchemy

 Background in econometrics or experimental design

 Spark UI profiling and performance benchmarking

 CI/CD tooling (SonarCloud, Snyk, GitHub Actions)

What Sets You Apart

 You can look at a Spark execution plan and pinpoint why a job is OOM-ing

 You think in modules — clean separation of data processing, inference, and post-

processing

 You can go from a Jupyter notebook prototype to a production-grade, testable

service

 You're comfortable with both statistical rigor and software engineering best

practices

About Moative

Moative, an Applied AI Services company, designs AI roadmaps, builds co-pilots and predictive AI solutions for companies in energy, utilities, packaging, commerce, and other primary industries. Through Moative Labs, we aspire to build micro-products and launch AI startups in vertical markets. 

We have built and sold two companies, one of which was an AI company. Our founders and leaders are Math PhDs, Ivy League University Alumni, Ex-Googlers, and successful entrepreneurs.

Work you’ll do

As a data scientist, you will lead data-driven projects, design and develop advanced analytical frameworks and AI/ML solutions to address business problems. You will collaborate with product managers, engineers and domain experts to deliver intelligent solutions and products.

You’ll analyze new opportunities and ideas, evaluate new AI/ ML models/ frameworks/ platforms, conduct experiments, develop PoCs and prototypes.

As a Data Scientist, you will provide your advanced expertise on statistical and mathematical concepts and guide the team in AI/ML algorithms and model development. You will stay up-to-date with the latest advancements in data science, machine learning, and AI.

The ideal candidate will have a strong background in statistics, machine learning, and programming, as well as excellent business understanding and product design thinking skills. If you are passionate about data and have a proven track record of delivering impactful data solutions, we would love to hear from you.

Responsibilities

• Frame problems before you model them. You will define the problem structure, identify the right success metric, and map failure modes — data drift, integration cost, adoption friction — before a single model is trained. Post-mortems are not your primary output; pre-mortems are.
• Own delivery end-to-end, including deployment. You will take models from scoping through production. If your best work is a notebook that never shipped, this role is not for you. You will own the last mile: deployment, monitoring, iteration in production.
• Sit embedded in client teams and hold the room. You will join client standups, present modelling choices to client leadership, and defend or revise your approach on the spot. You will be the technical voice accountable for outcomes — not a back-office supplier of models.
• Build accelerators and reusable frameworks, not one-offs. You will identify repeatable patterns across engagements and convert them into tools, templates, and internal infrastructure that make the next delivery faster and more defensible.
• Write and communicate with precision across audiences. You will produce decision memos, model cards, and post-mortems that are specific enough for an engineer and clear enough for a CFO. You will cover trade-offs, assumptions, and risks — in the same meeting, for both rooms, without dumbing either one down.
• Drive ML lifecycle discipline. You will establish and enforce best practices across model development, versioning, evaluation, and monitoring — and raise the bar for how the team thinks about model quality and production readiness.

Who you are

You are a data scientist who is passionate about using AI/ML to improve processes, products and delight customers. You have experience working with less than clean data, developing ML models, and orchestrating the deployment of them to production. You thrive on taking initiatives, are very comfortable with ambiguity and can passionately defend your decisions.

Requirements and skills

• 2+ years of hands-on data science with shipped production models. Evidence of models that moved from development to deployment with measurable business impact. "Worked on" does not qualify — you must have owned the outcome.
• Consumer-scale domain depth in a regulated or operationally sensitive business. Direct experience with one or more of: credit risk and portfolio modelling (PD/LGD/EAD, scorecards, alternative-data underwriting, collections or behavioural scoring) or retail and commerce modelling (demand forecasting with seasonality and promo effects, assortment and markdown optimisation, customer segmentation and LTV, returns prediction, pricing elasticity). You can read a delinquency curve, or a sell-through curve, or a cohort retention plot and know what it implies for the next model decision and the next business decision
• Production GenAI and agentic system experience beyond prompt engineering. Hands-on with retrieval design, eval harnesses, guardrails, and fine-tuning vs. prompting trade-offs. You understand the observability and cost discipline required to run these systems in production. Prompt engineering alone does not qualify.
• Cloud and MLOps fluency. Proficient across at least one major cloud (AWS, Azure, or GCP) and experienced with MLOps tooling — MLflow, model registries, CI/CD for ML, and drift monitoring in production.
• Client-facing delivery experience. Has worked directly with external clients or business stakeholders — not just internal teams. Comfortable presenting technical choices, fielding pushback, and adjusting in real time without losing the thread.
• Structural problem framing, not just modelling skill. Demonstrates the ability to define what problem is actually worth solving, choose the right analytical approach for the business context, and articulate why alternative approaches were rejected.

Working at Moative

Moative is a young company, but we believe strongly in thinking long-term, while acting with urgency. Our ethos is rooted in innovation, efficiency and high-quality outcomes. We believe the future of work is AI-augmented and boundary less.

Here are some of our guiding principles:

• Think in decades. Act in hours. As an independent company, our moat is time. While our decisions are for the long-term horizon, our execution will be fast – measured in hours and days, not weeks and months.
• Own the canvas. Throw yourself in to build, fix or improve – anything that isn’t done right, irrespective of who did it. Be selfish about improving across the organization – because once the rot sets in, we waste years in surgery and recovery.
• Use data or don’t use data. Use data where you ought to but not as a ‘cover-my-back’ political tool. Be capable of making decisions with partial or limited data. Get better at intuition and pattern-matching. Whichever way you go, be mostly right about it.
• Avoid work about work. Process creeps on purpose, unless we constantly question it. We are deliberate about committing to rituals that take time away from the actual work. We truly believe that a meeting that could be an email, should be an email and you don’t need a person with the highest title to say that out loud.
• High revenue per person. We work backwards from this metric. Our default is to automate instead of hiring. We multi-skill our people to own more outcomes than hiring someone who has less to do. We don’t like squatting and hoarding that comes in the form of hiring for growth. High revenue per person comes from high quality work from everyone. We demand it.

If this role and our work is of interest to you, please apply here. We encourage you to apply even if you believe you do not meet all the requirements listed above.

The position is based out of Chennai. Our work currently involves significant in-person collaboration and we expect you to be present in the city

Senior AI/ML Engineer

📍 Pune, Maharashtra (Onsite)

💼 Experience: 6–10 Years

🕒 Employment Type: Full-Time

About the Role

We are seeking a highly skilled Senior AI/ML Engineer to lead the design, development, and deployment of enterprise-scale Artificial Intelligence and Machine Learning solutions. The ideal candidate will possess strong expertise in production-grade Retrieval-Augmented Generation (RAG) systems, deep learning architectures, semantic search platforms, vector databases, and AI orchestration frameworks.

This role requires hands-on technical leadership, architectural ownership, and proven experience building scalable AI systems that operate reliably in production environments.

Key Responsibilities

• Design and architect enterprise-grade RAG (Retrieval-Augmented Generation) solutions
• Build and optimize document chunking, retrieval, reranking, and hallucination mitigation pipelines
• Develop and deploy machine learning models using XGBoost, PyTorch, and TensorFlow
• Design deep learning solutions including LSTM and transformer-based architectures
• Build semantic search and vector retrieval systems using modern vector databases
• Develop advanced AI workflows using LangChain and LangGraph
• Design and implement multi-agent AI systems and orchestration frameworks
• Lead AI model deployment, monitoring, optimization, and lifecycle management
• Collaborate with cross-functional teams to translate business requirements into scalable AI solutions
• Mentor junior engineers and contribute to technical leadership initiatives
• Drive AI architecture decisions, performance tuning, and best practices

Required Skills & Qualifications

Must-Have Technical Skills

• 6–10 years of software engineering and AI/ML development experience
• Strong experience building and deploying production AI/ML systems
• Hands-on expertise with RAG architectures and semantic retrieval systems
• Experience with vector databases such as Pinecone, Weaviate, Chroma, Milvus, or Qdrant
• Strong knowledge of Machine Learning and Deep Learning concepts
• Hands-on experience with:
• PyTorch and/or TensorFlow
• XGBoost
• LangChain
• LangGraph
• Experience deploying AI applications in production environments
• Strong debugging, performance optimization, and troubleshooting skills
• Excellent Python programming skills
• Understanding of REST APIs, microservices, and scalable system design

Preferred Skills

• MLflow
• Weights & Biases (W&B)
• Kubeflow
• Transformer architectures and LLM internals
• MLOps practices and model lifecycle management
• Multi-agent AI frameworks
• Cloud platforms such as AWS, Azure, or GCP
• Docker and Kubernetes
• CI/CD pipelines for AI applications

Ideal Candidate Profile

You are someone who:

• Has successfully deployed AI solutions into production environments
• Understands enterprise-scale AI architecture and design patterns
• Has practical experience with retrieval systems and vector search
• Can independently drive AI initiatives from concept to deployment
• Enjoys solving complex engineering challenges
• Demonstrates strong ownership, leadership, and mentoring capabilities
• Thrives in a fast-paced product and engineering environment

Who Should Not Apply

• Prompt-engineering-only profiles
• Candidates with only academic or research exposure
• Tutorial/demo-level GenAI practitioners
• Engineers without production deployment experience
• Professionals lacking hands-on implementation expertise

Educational Qualification

• B.E. / B.Tech in Computer Science, Information Technology, Artificial Intelligence, Machine Learning, Data Science, or related discipline
• Master's degree is a plus

Work Location

📍 Pune, Maharashtra (Onsite)

Hiring Preference

• Immediate joiners preferred
• Candidates currently working on production AI/ML systems will be given preference

Keywords

AI Engineer, Senior AI Engineer, Machine Learning Engineer, Generative AI Engineer, LLM Engineer, RAG Engineer, LangChain, LangGraph, Vector Database, Semantic Search, Deep Learning, PyTorch, TensorFlow, XGBoost, ML Engineer, AI Architect, MLOps, Multi-Agent Systems, Production AI

We're Hiring | AI/ML Engineer (Training & Development) – Female Candidate Preferred

We are looking for a passionate and skilled Female AI/ML Engineer who can conduct engaging training sessions while also contributing to AI/ML development projects. The ideal candidate should have strong technical expertise along with excellent communication and presentation skills.

Experience: 2–3 Years

Key Skills: Python, Machine Learning, Deep Learning, Generative AI, LLMs, NLP, Computer Vision, LangChain, RAG, Prompt Engineering, TensorFlow, PyTorch, Scikit-learn

Training Expertise: Ability to deliver training sessions on AI/ML, Data Science, Python, Generative AI, and emerging technologies using various AI tools and platforms.

Preferred: Candidates with experience in both training and development activities.

📍 Location: Jaipur (On-site)

💻 Laptop Provided by Company

📅 Working Days: Monday to Saturday

💰 Salary: ₹25,000 – ₹30,000 per month

Role & Responsibilities

Responsibilities

• Contribute to the development and optimization of enterprise-wide search systems and models.

• Design and implement algorithms to improve indexing, query relevance, and search accuracy.

• Support taxonomy, ontology, and metadata model creation for better search outcomes.

• Collaborate with business units (Loans, Insurance, Investments) to build AI-enabled search features.

• Conduct analysis of user behavior and system metrics to refine search performance.

• Work with engineers, product managers, and designers to deliver integrated search solutions.

• Develop production-grade ML systems for ranking, personalization, and recommendations.

• Participate in proof-of-concept initiatives with internal and external partners.

• Follow best practices in software engineering including CI/CD, testing, and monitoring.

• Keep abreast of emerging developments in AI/ML to apply them in practical solutions.

Ideal Candidate

Strong Data Scientist / AI Engineer / Machine Learning Engineer profiles.

Mandatory (Experience 1) – Must have minimum 5+ years of hands-on experience in Data Science, Machine Learning, Applied AI, NLP, Deep Learning, or Generative AI solutions.

Mandatory (Experience 2) – Must have strong hands-on experience in Python programming, SQL, data analysis, feature engineering, model development, and production-grade ML applications.

Mandatory (Experience 3) – Must have experience working with Machine Learning and Deep Learning frameworks such as PyTorch, TensorFlow, Keras, Scikit-learn, or equivalent.

Mandatory (Experience 4) – Must have hands-on experience working on NLP, embeddings, semantic search, text classification, document understanding, recommendation systems, or similar AI/ML use cases.

Mandatory (Experience 5) – Must have experience working with Large Language Models (LLMs) such as GPT, Llama, Mistral, Claude, Gemini, Phi, or similar foundation models.

Mandatory (Experience 6) – Must have hands-on experience building or implementing RAG (Retrieval Augmented Generation) systems, vector search, knowledge retrieval, embeddings, chunking, indexing, or semantic retrieval solutions.

Mandatory (Experience 7) – Must have experience working with Git, CI/CD practices, production environments, and scalable AI/ML systems.

Mandatory (CTC) – The CTC breakup offered will be 75% fixed + 25% variable, as per company policy.

Mandatory (Age) - Candidate's Age should be below 30 Years

Preferred (Experience 1) – Experience with MLFlow, Kubeflow, Airflow, Prefect, Feature Stores, Model Registry, or MLOps/LLMOps frameworks.

Preferred (Experience 2) – Experience working with Vector Databases, Spark, PySpark, distributed ML pipelines, large-scale data processing, or real-time ML systems..

Preferred (Experience 3) – Familiarity with Docker, Kubernetes, Azure, AWS, GCP, cloud-native AI deployments, and scalable ML architecture.

Preferred (Company) – Candidates from AI-first startups, Fintech, Banking, Lending, Fraud Analytics, Risk Analytics, Product Companies, SaaS organizations, or data-driven technology companies.

Kindly provide the following details while sending your CV: (Mandatory details)

1) Date of Birth

2) Current Location-

3) Current CTC-

4) Expected CTC-

5) Notice Period-

6) Ready to relocate to Pune?

Regards,

The Supreme Consultancy

Website- https://lnkd.in/eawfxfxU

About NonStop io Technologies

NonStop io Technologies is a value-driven company with a strong focus on process-oriented software engineering. We specialize in Product Development and have a decade's worth of experience in building web and mobile applications across various domains. NonStop io Technologies follows core principles that guide its operations and believes in staying invested in a product's vision for the long term. We are a small but proud group of individuals who believe in the 'givers gain' philosophy and strive to provide value in order to seek value. We are committed to and specialize in building cutting-edge technology products and serving as trusted technology partners for startups and enterprises. We pride ourselves on fostering innovation, learning, and community engagement. Join us to work on impactful projects in a collaborative and vibrant environment.

Brief Description:

We're seeking an AI/ML Engineer to join our team. As AI/ML Engineer, you will be responsible for designing, developing, and implementing artificial intelligence (AI) and machine learning (ML) solutions to solve real-world business problems. You will work closely with engineering teams, including software engineers, domain experts, and product managers, to deploy and integrate Applied AI/ML solutions into the products that are being built at NonStop io. Your role will involve researching cutting-edge algorithms and data processing techniques, and implementing scalable solutions to drive innovation and improve the overall user experience.

Responsibilities

● Applied AI/ML engineering; Building engineering solutions on top of the AI/ML tooling available in the industry today. Eg: Engineering APIs around OpenAI

● AI/ML Model Development: Design, develop, and implement machine learning models and algorithms that address specific business challenges, such as natural language processing, computer vision, recommendation systems, anomaly detection, etc.

● Data Preprocessing and Feature Engineering: Cleanse, preprocess, and transform raw data into suitable formats for training and testing AI/ML models. Perform feature engineering to extract relevant features from the data

● Model Training and Evaluation: Train and validate AI/ML models using diverse datasets to achieve optimal performance. Employ appropriate evaluation metrics to assess model accuracy, precision, recall, and other relevant metrics

● Data Visualization: Create clear and insightful data visualizations to aid in understanding data patterns, model behaviour, and performance metrics

● Deployment and Integration: Collaborate with software engineers and DevOps teams to deploy AI/ML models into production environments and integrate them into various applications and systems

● Data Security and Privacy: Ensure compliance with data privacy regulations and implement security measures to protect sensitive information used in AI/ML processes

● Continuous Learning: Stay updated with the latest advancements in AI/ML research, tools, and technologies, and apply them to improve existing models and develop novel solutions

● Documentation: Maintain detailed documentation of the AI/ML development process, including code, models, algorithms, and methodologies for easy understanding and future reference.

Qualifications & Skills

● Bachelor's, Master's, or PhD in Computer Science, Data Science, Machine Learning, or a related field. Advanced degrees or certifications in AI/ML are a plus

● Proven experience as an AI/ML Engineer, Data Scientist, or related role, ideally with a strong portfolio of AI/ML projects

● Proficiency in programming languages commonly used for AI/ML. Preferably Python

● Familiarity with popular AI/ML libraries and frameworks, such as TensorFlow, PyTorch, scikit-learn, etc.

● Familiarity with popular AI/ML Models such as GPT3, GPT4, Llama2, BERT etc.

● Strong understanding of machine learning algorithms, statistics, and data structures

● Experience with data preprocessing, data wrangling, and feature engineering

● Knowledge of deep learning architectures, neural networks, and transfer learning

● Familiarity with cloud platforms and services (e.g., AWS, Azure, Google Cloud) for scalable AI/ML deployment

● Solid understanding of software engineering principles and best practices for writing maintainable and scalable code

● Excellent analytical and problem-solving skills, with the ability to think critically and propose innovative solutions

● Effective communication skills to collaborate with cross-functional teams and present complex technical concepts to non-technical stakeholders

About the Role

Viamagus is a fully AI-driven engineering organization.

We're hiring a Technical Architect who has built real systems, deployed them to production, and meaningfully integrated AI into their engineering practice. You'll lead architecture across all client engagements.

Must-Have: Engineering Foundation

• Bachelor's in CS/Engineering or related field (Master's preferred)
• 8+ years of software development, 3+ years in an architect/lead role
• Built systems from scratch and taken them to production - owned the full lifecycle, not just slices
• Multiple integration experiences - third-party APIs, enterprise systems (SAP, Salesforce, ERP), messaging/event buses, legacy modernization
• Built frameworks for scalability - reusable platforms, SDKs, shared libraries, and internal developer tooling adopted across teams
• Technology-agnostic strength - strong across at least one modern backend stack, one frontend framework, and one cloud platform; able to pick the right tool for the job rather than defaulting to favourite
• AWS or Azure cloud architecture - VPC design, IAM, container orchestration, cost optimization
• DevOps fluency: Docker, Jenkins/GitHub Actions, IaC (Terraform/CDK)
• Performance tuning, distributed tracing, structured logging, APM tools (Datadog, New Relic, or equivalent)
• AppSec collaboration - OWASP Top 10, VAPT remediation, secrets management, compliance (ISO/SOC 2/HIPAA exposure a plus)

Must-Have: AI-Era Awareness

You will be expected to architect systems that use AI effectively and lead engineers who do the same. Working knowledge of several of these is required:

• AI-assisted development - daily driver of Claude Code, Cursor, Copilot, or equivalent; can articulate where they help, where they fail, and how to get better outcomes from them
• LLM integration patterns - understanding of when to use OpenAI, Anthropic, Gemini, or open-source models; familiarity with API usage, streaming, function calling, structured outputs
• RAG basics — vector DBs (pgvector, Pinecone, Qdrant), embeddings, chunking, retrieval tradeoffs — enough to review and guide RAG implementations
• Agentic systems awareness — conceptual understanding of tool use, multi-step agents, and frameworks like LangGraph or CrewAI
• MCP (Model Context Protocol) — awareness of what it is and where it fits
• Prompt engineering fundamentals — versioning prompts, structured outputs, guardrails, handling hallucinations
• AI evaluation and cost awareness — how to measure quality, latency, and cost of LLM-powered features
• Curiosity and experimentation mindset — has tried things beyond ChatGPT in a browser tab

Responsibilities

Architecture & Delivery

• Design scalable, secure architectures for client engagements
• Lead technical due diligence on proposals - feasibility, effort estimation, risk flagging
• Drive production readiness: incident management, observability, release processes
• Review and approve high-impact design decisions across projects

Team & Stakeholders

• Mentor 15–20 engineers across backend, mobile, and cloud teams
• Conduct architecture reviews, code reviews, and technical retrospectives
• Engage directly with client CTOs/architects on solution design and technical escalations
• Translate business objectives into architectural decisions and vice versa

Quality, Risk, Compliance

• Enforce security-first design - threat modelling, data classification, AI-specific risks (prompt injection, PII leakage, model supply chain)
• Ensure compliance readiness for ISO 27001, SOC 2, HIPAA, where applicable
• Identify and mitigate delivery risks early; escalate with proposed mitigations

Nice to Have

• Contributions to open-source projects or AI tooling
• Experience with real-time sync (CRDTs, Realm, Ditto) or offline-first architectures
• Published technical content - blogs, talks, GitHub
• Google/AWS/Azure certifications (bonus, not substitute)

Amura’s Vision 

We believe that the most under-appreciated route to releasing untapped human potential is to build a healthier body, and through which a better brain. This allows us to do more of everything that is important to each one of us.

Billions of healthier brains, sitting in healthier bodies, can take up more complex problems that defy solutions today, including many existential threats, and solve them in just a few decades.

Billions of healthier brains will make the world richer beyond what we can imagine today. The surplus wealth, combined with better human capabilities, will lead us to a new renaissance, giving us a richer and more beautiful culture.

These healthier brains will be equipped with deeper intellect, be less acrimonious, more magnanimous, and have a kinder outlook on the world, resulting in a world that is better than any previous time.

We find this vision of the future exhilarating. Our hopes and dreams are to create this future as quickly as possible and ensure that it is widely distributed and optimized to maximize all forms of human excellence. 

Role Overview 

We are looking for a highly skilled Senior DevOps Engineer (AI-Native Infrastructure & Platform Engineering) with deep expertise in AWS cloud infrastructure, automation, AI infrastructure operations, and modern DevOps/SRE practices.

This role goes beyond traditional DevOps and requires a seasoned specialist capable of building and operating AI-ready infrastructure platforms that support high-throughput APIs, LLM/AI workloads, GPU-based compute, data-intensive systems, real-time inference pipelines, and scalable ML platforms.

You will be responsible for architecting, automating, securing, and optimizing highly scalable and cost-efficient cloud environments that enable high-velocity engineering and AI teams. This is an ideal position for someone who combines technical ownership, an automation-first mindset, and a passion for developer productivity and platform reliability. 

Key Responsibilities 

Cloud Infrastructure & Platform Engineering (AWS) 

• Architect, deploy, and manage highly scalable and secure infrastructure on AWS. Design cloud platforms supporting AI/ML workloads, data pipelines, real-time APIs, and high-concurrency backend systems.
• Hands-on expertise with key AWS services including EC2, ECS/EKS, Lambda, RDS, DynamoDB, S3, VPC, CloudFront, IAM, CloudWatch, and GPU-enabled instances.
• Build and maintain Infrastructure-as-Code (IaC) using Terraform, CloudFormation, or AWS CDK.
• Design multi-AZ and multi-region architectures for high availability and disaster recovery (HA/DR).
• Build reusable platform templates and shared infrastructure modules. 

AI/ML Infrastructure & MLOps 

• Build and maintain infrastructure for LLM applications, AI inference workloads, model serving platforms, vector databases, and feature stores.
• Support GPU-based workloads and optimize compute/storage usage.
• Enable scalable deployment patterns for AI applications using Kubernetes/EKS. Collaborate with Data Science and ML Engineering teams on model deployment, training/tuning of models, CI/CD for ML systems, experiment environments, and reproducibility.
• Support orchestration and deployment of AI workflows and inference services while implementing observability and reliability for AI pipelines. 

CI/CD, Automation & Developer Productivity 

• Build and maintain CI/CD pipelines using GitHub Actions, GitLab CI, Jenkins, or AWS CodePipeline.
• Automate deployments, environment provisioning, and release workflows.
• Build self-service developer platforms, preview environments, and reusable deployment workflows to improve developer productivity.
• Implement automated patching, scaling, backups, cleanup workflows, and drift detection. 

Containers, Kubernetes & Platform Reliability

• Manage Docker-based environments, containerized applications, and optimize workloads using Kubernetes (EKS) or ECS/Fargate.
• Manage autoscaling, cluster health, node pools, ingress, service mesh, and workload isolation.
• Optimize infrastructure for performance, resilience, and cost-efficiency.
• Implement progressive deployment strategies including blue/green, canary, and rolling deployments. 

Observability, Incident Response & SRE Practices

• Implement observability stacks using CloudWatch, Prometheus, Grafana, ELK, Datadog, OpenTelemetry, or New Relic.
• Build actionable dashboards and intelligent alerting systems while defining and tracking SLIs, SLOs, and SLAs.
• Lead incident response, root cause analysis, and blameless postmortems to reduce operational toil and improve MTTR.

FinOps, Cost Governance & Security

• Continuously monitor and optimize cloud costs (compute utilization, storage lifecycle, GPU usage, and data transfer) using AWS Cost Explorer, Budgets, Trusted Advisor, CloudHealth, or Kubecost.
• Implement AWS security best practices for IAM, VPCs, security groups, NACLs, encryption, and manage secrets using KMS, SSM Parameter Store, or Vault.
• Build secure CI/CD pipelines with automated security checks, least-privilege access, audit logging, and ensure compliance readiness for ISO 27001, SOC2, and GDPR.

Collaboration, Leadership & Platform Culture

• Work closely with engineering, AI/ML, QA, product, and operations teams to drive a DevOps, SRE, GitOps, and automation-first culture.
• Mentor junior DevOps and Platform Engineers while creating and maintaining detailed runbooks, architecture diagrams, and platform documentation.

Skills & Qualifications

Must-Have:

• 7+ years of experience in DevOps, SRE, Platform Engineering, or Cloud Infrastructure Engineering.
• Strong expertise in AWS cloud architecture, services, and deep understanding of Kubernetes (EKS), containers, and cloud-native systems.
• Strong Infrastructure-as-Code expertise using Terraform, CloudFormation, or CDK. Strong Linux administration, networking, DNS, routing, and load balancing knowledge. Strong scripting/programming experience in Python, Bash, or Go (preferred). Experience with CI/CD automation, GitOps workflows, and observability platforms supporting scalable production systems.

Preferred / Nice-to-Have:

• Experience with AI/ML infrastructure, MLOps, model serving, vector databases, GPU orchestration, and inference optimization.
• Familiarity with Kafka, Redis, SQS, and event-driven systems.
• Exposure to platform engineering, internal developer platforms, and tools like ArgoCD, Flux, Helm, and OpenTelemetry.
• AWS Certifications: Solutions Architect, DevOps Engineer, or SysOps Administrator. Knowledge of distributed systems and large-scale platform operations. 

Preferred / Nice-to-Have:

• Experience with AI/ML infrastructure, MLOps, model serving, vector databases, GPU orchestration, and inference optimization.
• Familiarity with Kafka, Redis, SQS, and event-driven systems.
• Exposure to platform engineering, internal developer platforms, and tools like ArgoCD, Flux, Helm, and OpenTelemetry.
• AWS Certifications: Solutions Architect, DevOps Engineer, or SysOps Administrator. Knowledge of distributed systems and large-scale platform operations. 

Here are answers to some questions you may have

Where is your office?

Chennai (Velachery)

Work Model

Work from Office – because great stories are built in person!

Do you have an online presence?

https://amura.ai (we are @AmuraHealth on all social media)

We are looking for a highly skilled and experienced Senior AIOps / MLOps Engineer with strong expertise in Azure Cloud, automation, platform engineering, CI/CD, observability, and enterprise-scale cloud operations.

The ideal candidate should have hands-on experience in designing, implementing, and managing modern cloud-native platforms with focus on AI/ML operationalization, DevOps automation, monitoring, reliability, and infrastructure modernization.

Required Experience

• 6 – 10 Years of overall IT experience
• Strong experience in AIOps / MLOps / DevOps engineering
• Hands-on enterprise experience in Azure Cloud platform engineering

Key Responsibilities

AIOps / MLOps

• Design and implement scalable enterprise-grade AIOps and MLOps platforms across cloud environments.
• Ensure AI platform reliability, governance, security, and model performance optimization.
• Implement LLM/AI model versioning, experiment tracking, drift detection, observability, and operational health monitoring frameworks.
• Collaborate with Data Science, DevOps, Cloud, and Application teams to accelerate AI/ML adoption and platform modernization.
• Develop automation frameworks for AI/ML pipelines, infrastructure provisioning, and operational workflows.
• Lead continuous improvement, automation, and standardization efforts across AI/ML operational ecosystems
• Mentor engineering teams and promote AIOps/MLOps best practices, innovation, and engineering excellence
• Strong Knowledge on embeddings, tokenization, vector databases, and AI/ML model training concepts

Preferred Skills

• Python, MLflow, Model Registry, Experiment Tracking
• Azure DevOps & Azure Cloud
• Azure Machine Learning
• LLMOps / Generative AI operationalization
• AI model deployment and lifecycle management
• AI Gateway and Model Serving architectures
• Azure OpenAI & Azure AI Foundry
• MCP Server implementation and configuration  
• CI/CD Automation & AKS

Soft Skills

• Strong communication and stakeholder management
• Good troubleshooting and problem-solving skills
• Ability to work independently and drive ownership
• Strong collaboration and documentation skills

Position Title: Data Science Trainer

Company: TeksAcademy

Location: Hyderabad

Employment Type: Full-Time (Onsite)

About the Role:

We’re looking for an experienced and passionate Data Science Trainer to lead learning initiatives, impart industry-relevant knowledge, and build foundational and advanced skills in data science for our learners. As a Data Science Trainer, you’ll guide individuals or groups through the concepts and techniques needed to succeed in data analysis, machine learning, and data-driven decision-making.

Key Responsibilities:

• Conduct Data Science Training: Lead both online and in-person training sessions on a variety of data science topics such as statistics, programming (Python, R), machine learning, data visualization, and more.
• Create and Curate Course Materials: Develop and update educational resources, such as slides, tutorials, exercises, and datasets, ensuring they align with the latest industry standards.
• Facilitate Hands-On Learning: Engage learners with practical coding exercises and real-world problem-solving tasks to enhance their understanding of data science techniques.
• Assess and Provide Feedback: Evaluate students' progress through assessments, quizzes, and projects, giving personalized feedback to help them improve their skills.
• Stay Current with Trends: Continuously learn about emerging trends, tools, and techniques in data science, integrating these into training materials and courses.
• Provide Mentorship: Offer mentorship to students, helping them build confidence in applying data science concepts, troubleshooting issues, and building portfolios of their work.
• Collaborate and Improve: Work closely with other instructors, curriculum designers, and teams to improve and refine training programs, based on feedback and results.

Required Qualifications:

• Educational Background: Bachelor’s or Master’s degree in Data Science, Computer Science, Statistics, Mathematics, or a related field.
• Experience: Demonstrated experience in data science, machine learning, statistical analysis, and working with data programming languages such as Python, R, and SQL.
• Teaching Experience: Proven track record of teaching or training in a technical field, especially data science, either online or in-person.
• Technical Expertise: Strong hands-on experience with data science tools and libraries like Pandas, NumPy, Scikit-learn, Matplotlib, Tensor Flow, etc.

About Us: Website: https://www.tundratechnical.ca/ & https://tundramanagedsolutions.com/

Experience: 5-8 years

Shift: EST

Location: Bangalore

Mode: Hybrid

Position Requirements

Core (Must-Have) Skills

• Proficiency in Python with advanced use of NumPy, Pandas, and Scikit-learn

• Expertise in SQL, including complex queries and performance optimization

• Strong foundation in machine learning techniques (regression, classification, clustering, ensemble methods)

• Natural Language Processing (NLP), Large Language Models (LLMs), and Generative AI

• MLOps practices (MLFlow, Kubeflow, CI/CD pipelines for ML workflows)

• Experience in data visualization (Seaborn, Plotly, Tableau, or Power BI)

• Applied knowledge of statistics and probability for model development

• Hands-on experience with cloud-based ML platforms (AWS SageMaker, Azure ML, or GCP Vertex AI)

• Exposure to large-scale data processing (Spark, Hadoop)

Preferred Skills

• Deep learning frameworks (TensorFlow, PyTorch)

• Natural Language Processing (NLP), Large Language Models (LLMs), and Generative AI

• MLOps practices (MLFlow, Kubeflow, CI/CD pipelines for ML workflows)

• Data pipeline orchestration (Airflow, Prefect)

• Business domain knowledge (e.g., retail, finance)

Key Activities

• Preparing and preprocessing structured and unstructured data for analysis

• Designing, training, and validating machine learning models

• Deploying and operationalizing models in collaboration with engineering teams

• Building dashboards and data-driven visual insights for stakeholders

• Partnering with product and engineering teams to align models with business needs

• Monitoring, optimizing, and retraining models for performance improvements

We are looking for a hands-on Associate / Architect – Generative AI to design, build, and deploy enterprise-grade GenAI platform capabilities across multiple business units. This role focuses on developing scalable and reusable AI components across the full stack, covering RAG systems, agent orchestration, LLM infrastructure, and GenAIOps on GCP (primary) and Azure.

Key Responsibilities

• Design and build production-ready Generative AI systems and platform components
• Develop and deploy scalable RAG pipelines including data ingestion, embeddings, retrieval, and APIs
• Build agentic AI systems with orchestration, routing, memory, and workflow management
• Develop and manage LLM infrastructure including model routing, caching, observability, and rate limiting
• Build scalable backend services and APIs for AI-driven applications
• Implement GenAIOps/MLOps practices including prompt management, evaluation, monitoring, and deployment
• Work extensively with GCP services such as Vertex AI, BigQuery, Cloud Run, GKE, and Pub/Sub
• Ensure AI governance, safety, compliance, PII protection, and auditability standards are maintained
• Design scalable enterprise AI architectures with strong focus on performance, reliability, and reusability
• Collaborate with cross-functional teams to deliver enterprise-grade AI solutions
• Mentor junior engineers and contribute to technical leadership, architecture discussions, and design reviews

Required Skills & Experience

• Strong hands-on experience building and deploying production-grade Generative AI and RAG systems
• Experience working on multi-agent or agentic AI architectures
• Strong proficiency in Python and backend/API development
• Hands-on experience with GCP AI/ML ecosystem including Vertex AI and BigQuery
• Solid understanding of LLM infrastructure, orchestration layers, and AI platform engineering
• Experience with CI/CD pipelines and Infrastructure as Code tools like Terraform
• Good understanding of GenAIOps/MLOps practices and model lifecycle management
• Strong system design and architecture experience for scalable AI platforms
• Exposure to enterprise application architecture and distributed systems
• Experience leading small engineering teams, mentoring developers, or owning technical delivery is preferred
• Understanding of AI safety, governance, and compliance best practices

Nice to Have

• Experience with LangChain, LlamaIndex, or similar frameworks
• Familiarity with RAG evaluation tools such as RAGAS or DeepEval
• Knowledge of Knowledge Graphs with RAG systems
• Experience working in multi-cloud environments (GCP + Azure)
• Exposure to BFSI or other regulated domains

What We’re Looking For

• Engineers who have built and deployed real-world GenAI systems at scale
• Strong backend engineering and systems-thinking mindset
• Ability to thrive in fast-paced enterprise environments
• Ownership mindset with strong communication and collaboration skills 

About Swarmlens

At Swarmlens, we are building next-generation intelligent systems powered by Artificial Intelligence, Machine Learning, and Generative AI. Our mission is to create scalable, impactful, and production-ready AI solutions that solve real-world business challenges.

Role Overview

We are looking for a highly skilled Senior Generative AI Engineer with strong hands-on expertise in building and deploying Gen AI applications at scale. The ideal candidate should have deep experience working with LLMs, RAG pipelines, AI agents, prompt engineering, and production-grade AI systems.

You will work across the complete AI lifecycle — from model development and orchestration to deployment and optimization — while contributing to cutting-edge AI innovation.

Key Responsibilities

-Build and deploy end-to-end Generative AI solutions.

-Develop LLM-powered applications and AI copilots.

-Design and implement RAG pipelines and AI agent workflows.

-Work on prompt engineering, evaluation frameworks, and model optimization.

-Develop scalable AI architectures and production-ready ML systems.

-Collaborate with cross-functional teams to deliver AI-driven products.

-Optimize AI models for performance, scalability, and reliability.

-Build intelligent automation systems using modern Gen AI frameworks.

Required Skills & Qualifications

-4–6 years of experience in AI/ML or Generative AI roles.

-Strong hands-on expertise in Generative AI and Large Language Models. (LLMs).

-Experience with RAG systems, AI Agents, Prompt Engineering, and Model Evaluation.

-Proficiency in Python and AI/ML frameworks such as PyTorch, TensorFlow, LangChain, LlamaIndex, etc.

-Strong understanding of Machine Learning, Deep Learning, NLP, and data pipelines.

-Experience in deploying production-grade AI applications.

-Knowledge of vector databases, orchestration frameworks, and cloud environments is a plus.

-Strong analytical, problem-solving, and system design mindset.

Mandatory Requirement-

Candidates holding 4–6 years of relevant experience with a strong command of Generative AI are only preferred for this position. Please apply only if you have relevant hands-on experience in the same domain.

Why Join Us?

-Work on cutting-edge AI and Gen AI technologies.

-Opportunity to build impactful real-world AI products.

-Collaborative and innovation-driven work culture.

-Exposure to advanced AI research and scalable deployments.

-Career growth in a fast-growing AI startup environment.

Senior Data Scientist (Remote – India) – Predictive Modeling & Machine Learning

Location: Remote (India)

Job Type: Full-time

Experience: 5+ Years

Job Summary:

We are looking for a highly skilled Senior Data Scientist to join our India-based team in a remote capacity. This

role focuses on building and deploying advanced predictive models to influence key business decisions. The

ideal candidate should have strong experience in machine learning, data engineering, and working in cloud

environments, particularly with AWS.

You'll be collaborating closely with cross-functional teams to design, develop, and deploy cutting-edge ML

models using tools like SageMaker, Bedrock, PyTorch, TensorFlow, Jupyter Notebooks, and AWS Glue. This is

a fantastic opportunity to work on impactful AI/ML solutions within a dynamic and innovative team.

Key Responsibilities:

Predictive Modeling & Machine Learning

• Develop and deploy machine learning models for forecasting, optimization, and predictive analytics.

• Use tools such as AWS SageMaker, Bedrock, LLMs, TensorFlow, and PyTorch for model training and

deployment.

• Perform model validation, tuning, and performance monitoring.

• Deliver actionable insights from complex datasets to support strategic decision-making.

Data Engineering & Cloud Computing

• Design scalable and secure ETL pipelines using AWS Glue.

• Manage and optimize data infrastructure in the AWS environment.

• Ensure high data integrity and availability across the pipeline.

• Integrate AWS services to support the end-to-end machine learning lifecycle.

Python Programming

• Write efficient, reusable Python code for data processing and model development.

• Work with libraries like pandas, scikit-learn, TensorFlow, and PyTorch.

• Maintain documentation and ensure best coding practices.

Collaboration & Communication

• Work with engineering, analytics, and business teams to understand and solve business challenges.

• Present complex models and insights to both technical and non-technical stakeholders.

• Participate in sprint planning, stand-ups, and reviews in an Agile setup.

Preferred Experience (Nice to Have):

• Experience with applications in the utility industry (e.g., demand forecasting, asset optimization).

• Exposure to Generative AI technologies.

• Familiarity with geospatial data and GIS tools for predictive analytics.

Qualifications:

• Master’s or Ph.D. in Computer Science, Statistics, Mathematics, or a related field.

• 5+ years of relevant experience in data science, predictive modeling, and machine learning.

• Experience working in cloud-based data science environments (AWS preferred).

About SkillSecureX

SkillSecureX is a technology-driven platform focused on providing practical learning experiences and industry-oriented opportunities in Artificial Intelligence, Machine Learning, Data Science, Web Development, and emerging technologies. We help students and freshers gain real-world exposure through hands-on projects, mentorship, and internship programs.

About the Internship

We are hiring motivated and enthusiastic candidates for the role of Artificial Intelligence & Machine Learning Intern. This internship is designed for students, freshers, and aspiring AI professionals who want to gain practical experience in AI technologies, Machine Learning concepts, and real-world project development.

Interns will work on practical assignments, AI-based applications, and industry-relevant projects while learning modern tools and technologies used in the AI and ML domain.

Roles & Responsibilities

• Assist in developing AI and Machine Learning models

• Work on data preprocessing and model training

• Analyze datasets and generate insights

• Support research and development activities related to AI solutions

• Work with Python libraries and AI frameworks

• Participate in project discussions and collaborative tasks

• Test, evaluate, and improve model performance

Required Skills

• Basic understanding of Python programming

• Interest in Artificial Intelligence and Machine Learning

• Familiarity with data analysis or statistics concepts is beneficial

• Knowledge of libraries such as NumPy, Pandas, or Scikit-learn is a plus

• Strong analytical and problem-solving skills

• Willingness to learn and work on practical projects

Eligibility

• Students pursuing graduation or post-graduation

• Freshers interested in AI and Machine Learning

• Candidates looking to gain practical industry exposure

Perks & Benefits

• Internship Completion Certificate

• Hands-on experience on practical AI projects

• Flexible remote working environment

• Mentorship and industry-oriented learning

• Opportunity to strengthen technical and professional skills

Title: Sr. Python Developer (Full-Stack & AI)

Location: Onsite – Mumbai, Maharashtra (Western Line)

Experience: 2 - 5+ years

Pay: ₹400,000.00 - ₹600,000.00 per year

Joining: Immediate

About the Role

We are building AI products for enterprise use and need a Senior Python Developer for our core team. You will be responsible for the full-stack architecture—designing both the backend and frontend. We want someone who works smart by using AI tools to build fast, but also has great skills to code manually when the logic is complex or needs high precision.

Key Responsibilities

• Build and maintain full-stack applications using Python and Django.
• Use AI-powered IDEs and development tools as your primary method to ship code quickly.
• Perform manual coding and deep debugging for complex logic that AI cannot handle alone.
• Collaborate with AI/ML teams to put machine learning models into production.
• Design how the entire system (frontend, backend, and database) works together.
• Optimize the application for speed, security, and reliability.
• Participate in technical discussions and help make architecture decisions.

Required Skills & Experience

• Minimum 5 years of professional Python development experience.
• Strong expertise in Django (Primary) and experience with FastAPI or Flask.
• Full-stack capability: Ability to design and build both the frontend and backend.
• Modern Tooling: High proficiency in using AI-powered IDEs and AI dev-agents to speed up your workflow.
• Manual Coding: Strong ability to write clean, manual code for complex backend logic.
• Solid understanding of databases like PostgreSQL, MySQL, or Redis.
• Familiarity with Cloud platforms (AWS/Azure/GCP) and Docker.
• Experience or strong interest in AI/ML pipeline integration.

Good to Have

• Experience with React or Next.js for the frontend.
• Exposure to message brokers like RabbitMQ or Kafka.
• Knowledge of Vector databases or RAG pipelines.
• Experience with CI/CD and basic DevOps.

Experience:

• Total: 3 years (Required)
• Python/Django: 3 years (Required)

Work Location: In person (Borivali, Mumbai)

About the Internship

LetsIntern is looking for passionate and motivated candidates for the AI & Machine Learning Internship Program. This internship is designed for students, freshers, and aspiring AI professionals who want hands-on experience working on real-world AI and Machine Learning projects.

Interns will gain exposure to practical AI workflows, data-driven problem solving, and industry-standard development practices under expert mentorship.

Roles & Responsibilities

✔ Assist in developing AI & Machine Learning models

✔ Work on real-world datasets and predictive analytics tasks

✔ Perform data preprocessing, cleaning, and visualization

✔ Support AI-based application development and testing

✔ Research and implement Machine Learning algorithms

✔ Collaborate with mentors and project teams on live tasks

✔ Prepare reports, insights, and documentation for projects

Skills & Technologies

• Python Programming

• Machine Learning Fundamentals

• Data Analysis & Visualization

• NumPy, Pandas, Matplotlib

• Deep Learning Basics

• NLP & Computer Vision (Basics)

• Model Training & Evaluation

Eligibility Criteria

✔ Students pursuing any degree (CS/IT preferred)

✔ Freshers interested in AI & ML

✔ Candidates passionate about Artificial Intelligence & Data Science

✔ Basic programming knowledge is a plus

✔ Strong willingness to learn and work on projects

What You’ll Gain

✔ Hands-on experience with AI & ML projects

✔ Live training sessions & mentorship

✔ Exposure to industry tools and workflows

✔ Internship Certificate

✔ Letter of Recommendation based on performance

✔ Opportunity to build a strong AI project portfolio

✔ Flexible & remote working environment

We are looking for an experienced Business Analyst with 10+ years of experience to lead AI product initiatives and guide the BA team. The role involves understanding business needs, gathering requirements, creating documents like BRDs, FRDs, and user stories, and coordinating with teams such as engineering, AI/ML, QA, design, and product.

The candidate should have knowledge of AI/ML concepts, strong stakeholder management skills, and experience building products from scratch. They will also mentor junior BAs, conduct UAT testing, support Agile/Scrum processes, and help deliver AI-driven solutions successfully.

Key responsibilities include:

• Requirement gathering and solution analysis
• Stakeholder communication and workshops
• Documentation and project coordination
• UAT and QA support
• Team leadership and mentoring
• Working on AI-powered products and automation solutions
• Ensuring ethical and compliant AI practices

Preferred experience includes exposure to Generative AI, LLMs, AI agents, SaaS products, and tools like Jira, Confluence, Figma, and Miro. 

Technical Product Manager

A senior individual contributor role at the intersection of product direction, engineering process, and client outcomes. You will be the person who turns ambiguity into shipped features — and keeps a growing platform from accumulating invisible debt.

Looking for someone who:

– Has managed a tech team through a structural process change and can speak specifically about what broke, what they changed, and what improved

– Has taken a product from its first documentation-zero state to a well-documented, institutionally resilient one

– Has sat in a difficult client conversation where the client wanted something unreasonable — and held the line without losing the relationship

– Has managed someone who pushed back on being managed, and has a specific, unsanitised story about how it went

–Understands SSO/SAML, HRMS integration patterns or other enterprise integration complexity at a level sufficient to write a technical spec without engineering input

–Has used Jira (or equivalent) as a process governance tool — sprint velocity, bug classification, release notes, retrospective action tracking — not just a task list

– Has worked in L&D tech, HR tech, sales enablement or an adjacent SaaS vertical — understands that end users are often frontline workers with limited digital literacy

– Has Figma proficiency and can make design decisions on wireframes independently

Are you passionate about Artificial Intelligence and automation? We are looking for dedicated and eager-to-learn individuals to join our team for a 100-day internship as an AI Workflow Developer.

This is a strictly learning-focused, unpaid opportunity designed to give you practical, hands-on experience under expert guidance. If you want to bridge the gap between theoretical knowledge and real-world AI development, this is the perfect place to start.

📌 Internship Highlights:

• Role: AI Workflow Developer Intern
• Duration: 100 Days
• Work Mode: Flexible Remote
• Time Commitment: 5 hours per day
• Stipend: Unpaid (Learning and professional development focused)

💡 What We Offer:

• Expert Mentorship: Work directly with experienced developers who will guide you through modern development workflows and real-world problem-solving.
• Structured Courses: Gain access to specialized learning materials covering AI automation, API integrations, and the fundamentals of workflow architecture.
• Live Project Experience: Move beyond theory by contributing to practical AI integrations and agentic workflows.
• Certification: Receive a verified internship certificate upon successful completion of your 100-day journey.

🛠️ What You'll Be Doing:

• Learning to build, automate, and optimize AI-driven workflows.
• Exploring prompt engineering and integrating LLM APIs into functioning applications.
• Collaborating with the team on testing, troubleshooting, and deploying AI solutions.

🎯 Who Should Apply?

• Tech enthusiasts with a foundational understanding of programming (Python preferred) and basic AI concepts.
• Self-starters who are highly motivated, disciplined, and ready to dedicate 5 hours daily to their professional growth.

📩 How to Apply: Ready to accelerate your learning? Send your resume and a brief introduction to hello[@]thecodershub.co.in.

ML DEVELOPER

Hyperworks Imaging is a cutting-edge technology company based out of Bengaluru, India since 2016. Our team uses the latest advances in deep learning and multi-modal machine learning techniques to solve diverse real world problems. We are rapidly growing, working with multiple companies around the world.

JOB OVERVIEW

We are seeking a talented and results-oriented ML Developer to join our growing team in India. In this role, you will be responsible for developing and implementing new advanced ML algorithms and AI agents for creating AI assistants of the future. 

The ideal candidate will work on a complete ML pipeline starting from extraction, transformation and analysis of data to developing novel ML algorithms. The candidate will implement latest research papers and closely work with various stakeholders to ensure data-driven decisions and integrate the solutions into a robust ML pipeline.

RESPONSIBILITIES:

• Create AI agents using Model Context Protocols (MCPs), Claude Code, DsPy etc.
• Develop custom evals for AI agents.
• Build and maintain ML pipelines
• Optimize and evaluate ML models to ensure accuracy and performance.
• Define system requirements and integrate ML algorithms into cloud based workflows.
• Write clean, well-documented, and maintainable code following best practices

REQUIREMENTS:

• 2-3+ years of experience in data science, machine learning, or a similar role.
• Demonstrated expertise with python, PyTorch, and TensorFlow.
• Graduated/Graduating with B.Tech/M.Tech/PhD degrees in Electrical Engg./Electronics Engg./Computer Science/Maths and Computing/Physics
• Has done coursework in Linear Algebra, Probability, Image Processing, Deep Learning and Machine Learning.
• Has demonstrated experience with Model Context Protocols (MCPs), DSPy, AI Agents, MLOps etc

WHO CAN APPLY:

Only those candidates will be considered who,

• have relevant skills and interests
• can commit full time
• Can show prior work and deployed projects
• can start immediately

Please note that we will reach out to ONLY those applicants who satisfy the criteria listed above.

SALARY DETAILS: Commensurate with experience.

JOINING DATE: Immediate

JOB TYPE: Full-time

Job Overview:

We are looking for a high-ownership Software Engineer with hands-on experience in modern full-stack development. The role demands strong fundamentals, the ability to work in a startup environment, and a mindset to build, iterate, and scale products.

You will be working closely with founders and cross-functional teams to build robust, scalable, and high-performance applications.

Core Responsibilities

·        Develop and maintain web applications using Next.js (frontend) and Nest.js (backend)

·        Design, build, and optimize RESTful APIs and backend services

·        Translate business requirements into scalable technical solutions

·        Collaborate with product, design, and business teams for feature development

·        Debug, troubleshoot, and improve application performance

·        Ensure code quality through clean architecture, testing, and best practices

·        Participate in deployment, monitoring, and continuous improvement cycles 

Technical Requirements

·        Strong proficiency in JavaScript and TypeScript

·        Solid understanding of web fundamentals (HTML, CSS, APIs, browser behavior)

·        Hands-on experience with Next.js and Nest.js

·        Working knowledge of PostgreSQL or relational databases

·        Familiarity with Git and GitHub (version control workflows)

·        Understanding of API design principles and backend architecture

Good-to-Have Skills

·        Experience with deployment platforms (Digital Ocean, AWS, Docker, etc.)

·        Knowledge of authentication, authorization, and security practices

·        Exposure to CI/CD pipelines

·        Understanding of scalable system design basics

What We Want

·        Strong problem-solving mindset

·        Ability to learn fast and adapt quickly

·        Comfort working in an unstructured startup environment

·        Ownership-driven attitude (not just task execution)

·        Clear communication and collaboration skills

Ideal Candidate Profile

·        Projects demonstrating end-to-end ownership

·        Contributions on GitHub (active repositories, clean code)

·        Experience building real-world applications (not just tutorials)

·        Ability to explain technical decisions and trade-offs

What You Will Get

·        Opportunity to work directly with startup founders

·        Fast-paced learning environment and accelerated skill development

·        Exposure to real product building and scaling challenges

·        Freedom to experiment, build, and innovate

·        Performance-driven growth and responsibility

·        Competitive compensation aligned with your potential

Additional Details

·        Joining: Immediate (7–15 days preferred)

·        Probation: 3 Months 

You will be at the forefront of Byteridge's AI infrastructure capabilities, helping customers unlock the full potential of foundation models through expert-level deployment on GPU infrastructure.

This highly technical role requires deep expertise in machine learning infrastructure, GPU optimization, and production ML systems, combined with the ability to translate complex technical concepts into customer success.

What You'll Do

Model Deployment & Optimization

• Lead end-to-end deployments of large language models on AWS infrastructure for strategic

customers

• Design and implement training, fine-tuning, and inference pipelines using Amazon SageMaker AI

• Optimize model performance through GPU-level tuning, kernel optimization, and infrastructure

configuration

• Deploy models on diverse GPU architectures including NVIDIA and AWS custom silicon (Trainium,

Inferentia)

Infrastructure Architecture & Performance

• Architect scalable ML infrastructure using SageMaker AI Inference, HyperPod, and distributed

training frameworks

• Implement CUDA-level optimizations and custom kernels for improved model performance

• Design storage and networking architectures optimized for high-throughput ML workloads

• Troubleshoot and resolve complex performance bottlenecks at the GPU driver and kernel level

Customer Engagement & Technical Leadership

• Partner with AWS AI Specialist Solution Architects and customer ML teams to understand model

requirements and deployment constraints

• Provide technical guidance on model selection, fine-tuning strategies, and production best practices

• Conduct performance benchmarking and cost optimization analysis for ML workloads

• Share field insights with AWS product teams to influence infrastructure and service roadmaps

What We're Looking For

Core Qualifications

• Bachelor's degree in Computer Science, Engineering, or equivalent practical experience (Master's or

PhD preferred)

• 5+ years of experience in machine learning infrastructure, model deployment, or GPU computing

• Strong programming skills in Python and experience with ML frameworks (PyTorch, TensorFlow, JAX)• Deep understanding of LLM architectures, training methodologies, and inference optimization

Technical Expertise (High-Level Alignment)

• Hands-on experience training, fine-tuning, or deploying large language models in production

• Proficiency with GPU programming, CUDA, and kernel-level optimization techniques

• Experience with distributed training frameworks and multi-GPU/multi-node orchestration

• Strong knowledge of AWS core services: EC2 (GPU instances), S3, EFS, VPC, and networking

Preferred Experience

• Direct experience with Amazon SageMaker AI (Training, Inference, HyperPod) or equivalent ML

platforms

• Understanding of GPU architectures (NVIDIA A100, H100) and AWS custom silicon (Trainium,

Inferentia)

• Experience with model compression techniques (quantization, pruning, distillation)

• Knowledge of MLOps practices, model monitoring, and production ML system design

• Background in high-performance computing, distributed systems, or systems programming

Essential Attributes

• Ability to dive deep into technical problems and debug complex infrastructure issues

• Strong analytical skills with data-driven approach to optimization

• Excellent communication skills to explain complex technical concepts to diverse audiences

• Comfortable working in ambiguous, fast-paced environments with evolving requirements

• Ownership mindset with ability to drive projects from architecture to production

Job Title: AI/ML Engineer (Forecasting)

Company: WINIT

Location: Hyderabad

Experience: 0–2 Years

Job Summary:

We are looking for a skilled AI/ML Engineer with strong expertise in demand forecasting, predictive analytics, and emerging Generative AI technologies. The ideal candidate should have hands-on experience in machine learning, deep learning, NLP, and LLM-based solutions, along with proficiency in Python, SQL, Power BI, and advanced Excel. This role involves building scalable forecasting models and leveraging AI/GenAI to deliver actionable business insights.

Key Responsibilities:

• Develop and deploy demand forecasting models using machine learning and deep learning techniques.
• Analyze historical data to identify trends, seasonality, and demand patterns.
• Build predictive models to improve supply chain and inventory planning.
• Work with large datasets using Python and SQL for data extraction, transformation, and analysis.
• Design dashboards and reports using Power BI for business stakeholders.
• Utilize advanced Excel techniques (Pivot Tables, Power Query, formulas) for analysis and reporting.
• Build and integrate NLP-based solutions for text data analysis and insights.
• Develop and implement LLM-based applications using Generative AI frameworks.
• Design and deploy RAG (Retrieval-Augmented Generation) pipelines for intelligent data retrieval and response generation.
• Collaborate with cross-functional teams (operations, finance, product) to align forecasting and AI solutions.
• Continuously improve model accuracy and performance through experimentation and optimization.

Required Skills:

• Strong proficiency in Python (Pandas, NumPy, Scikit-learn, TensorFlow/PyTorch).
• Solid understanding of machine learning & deep learning algorithms.
• Experience in demand forecasting / time-series analysis (ARIMA, Prophet, LSTM, etc.).
• Hands-on experience with NLP techniques and libraries (NLTK, SpaCy, Transformers).
• Experience working with LLMs and Generative AI frameworks (OpenAI, Hugging Face, LangChain, etc.).
• Strong understanding of RAG architectures and vector databases (FAISS, Pinecone, etc.).
• Advanced knowledge of SQL for data manipulation.
• Hands-on experience with Power BI for visualization and reporting.
• Expertise in advanced Excel (Power Query, dashboards, data modeling).
• Strong analytical and problem-solving skills. 

Preferred Qualifications:

• Experience in supply chain, logistics, or e-commerce forecasting.
• Knowledge of cloud platforms (AWS, Azure, or GCP).
• Familiarity with data pipelines and ETL processes.
• Understanding of business metrics and KPIs related to demand planning.

About WINIT

For more information, please visit: www.winitsoftware.com

About the Role

We are looking for a hands-on AI Agentic Lead to drive Agentic AI implementations on the Lyzr platform and lead in-house Agentic AI infusion into our products. This role is ideal for someone who combines strong technical depth with product thinking and has experience taking AI solutions from concept to deployment.

What We Are Looking For

• 6+ years to 15 years of overall experience
• At least 2 years of Agentic AI experience with product deployment exposure
• Strong experience in designing, building, and deploying AI agents/workflows for real business use cases
• Ability to lead architecture, development, deployment, and optimization of agentic solutions
• Strong problem-solving, ownership, and stakeholder-handling skills
• Interested to work in BENGALURU - WFO only.

Key Responsibilities

• Lead end-to-end delivery of Agentic AI solutions on the Lyzr platform
• Drive Agentic AI adoption across in-house products
• Design multi-agent workflows, orchestration patterns, tool usage, memory, guardrails, and evaluation approaches
• Work closely with product, business, and engineering teams to identify high-impact AI use cases
• Build scalable, production-ready solutions with focus on reliability, performance, and business value
• Mentor the team and shape best practices for Agentic AI delivery

Preferred Skills

• Hands-on experience with LLMs, AI agents, RAG, orchestration frameworks, prompt design, tool calling, and evaluation
• Exposure to production deployments, monitoring, debugging, and optimization of AI systems
• Experience integrating AI into enterprise products/platforms
• ML background is a plus, but not mandatory

Why Join Us

• Opportunity to work on live Agentic AI implementations
• Play a key role in building next-generation AI capabilities for both client solutions and internal products
• High ownership, strong growth opportunity, and direct impact on product direction

Location: Bangalore

Experience: 3-5 years

Type: Full-time | On-site

Start: Immediate

Why this role exists

Most companies are using LLMs.

Very few are building an advantage from them.

Right now, LLM cost is our largest margin constraint, and model behavior is still too generic to be defensible.

This role exists to:

• Turn LLM usage into a cost-efficient system
• Build compounding intelligence across accounts
• Create a differentiated analysis layer that competitors can’t replicate

What you’ll do

You will not just build models.

You will own the intelligence and cost structure of the platform.

1. Drive down LLM cost dramatically

• Reduce cost per interaction from ₹40 → ₹2 within 6 months
• Implement:
• Model tiering (right model for the right task)
• Caching strategies (semantic + response caching)
• Batching and async processing
• PTU / reserved capacity optimization
• Ensure performance does not degrade while reducing cost

2. Optimize infrastructure spend

• Reduce cloud spend from ₹20L/month → ₹4L/month
• Work across infrastructure layers (Azure / compute / inference)
• Balance:
• Latency
• Cost
• Throughput
• Treat infra as a first-class optimization problem

3. Build the fine-tuning and learning pipeline

• Design systems where:
• Every interaction improves future performance
• Build pipelines for:
• Fine-tuning
• Feedback loops
• Continuous model improvement
• Ensure the 5th customer deployment is structurally better than the 1st

4. Create a differentiated intelligence layer

• Build analysis systems that:
• Extract signals from interactions
• Improve decision-making
• Drive outcome improvements
• Move beyond responses → insight + action

5. Enable new AI-native product categories

• Identify opportunities where:
• AI enables workflows that were not previously possible
• Build foundational ML capabilities to unlock those categories
• Focus on creation, not just efficiency

6. Commoditize LLM usage internally

• Abstract complexity of LLM usage from product teams
• Build internal systems where:
• Cost is predictable
• Performance is consistent
• Make LLM usage a reliable utility layer

What success looks like

• Cost per interaction drops to ₹2 or lower
• Infrastructure spend reduces 5x without performance loss
• Model performance improves with every deployment
• Platform develops a clear intelligence advantage
• New AI-native capabilities become possible due to your systems

Who you are

• You have 3-5 years of experience in ML / applied AI / systems engineering
• You have worked with:
• LLMs
• Inference optimization
• Production ML systems
• You think in:
• Systems
• Trade-offs (cost vs latency vs quality)
• You care about real-world impact, not just model metrics

What will make you stand out

• Experience with:
• LLM optimization (prompting, fine-tuning, distillation)
• Distributed systems or infra-level optimizations
• High-scale inference systems
• Built systems that:
• Reduced cost significantly
• Improved performance over time
• Strong understanding of:
• Caching strategies
• Model routing
• Evaluation frameworks

Why join

• You will directly impact company margins and scalability
• Your work defines whether we have a defensible ML advantage
• You will build systems that move from:
• Generic AI usage → compounding intelligence

What this role is not

• Not research-only
• Not experimentation without production impact
• Not isolated from product and business outcomes

What this role is

• A builder of ML systems at scale
• A driver of cost and performance optimization
• A creator of long-term competitive advantage

One question to self-evaluate

Can you build ML systems that get cheaper, smarter, and more valuable with every interaction?

Want to work on exciting GenAI projects for Fortune 500 companies across multiple sectors? Then read on..

About Company:

CSG is a multi-national company having a presence in 20 countries with 1600+ Engineers. Company works with more than 40 Fortune 500 customers such as Sony, Samsung, ABB, Thyssenkrup, Toyota, Mitsubishi and many more.

Job Description:

We are looking for a talented Generative AI Developer to join our dynamic AI/ML team. This position offers an exciting opportunity to leverage cutting-edge Generative AI (GenAI) technologies to drive innovation to solve real world problems. You will be responsible for developing and optimizing GenAI-based applications, implementing advanced techniques like Retrieval-Augmented Generation (RAG), RIG (Retrieval Interleaved Generation), Agentic Frameworks and vector databases. This is a collaborative role where you will work directly with customers cross-functional teams to design, implement, and optimize AI-driven solutions. Exposure to cloud-native AI platforms such as Amazon Bedrock and Microsoft Azure OpenAI is highly desirable.

Key Responsibilities

Generative AI Application Development:

Design, develop, and deploy GenAI-driven applications to address complex industrial challenges.

Implement Retrieval-Augmented Generation (RAG) and Agentic frameworks

Data Management & Optimization:

Design and optimize document chunking strategies tailored to specific datasets and use cases.

Build, manage, and optimize data embeddings for high-performance similarity searches across vector databases.

Collaboration & Integration:

Work closely with data engineers and scientists to integrate AI solutions into existing pipelines.

Collaborate with cross-functional teams to ensure seamless AI implementation.

Cloud & AI Platform Utilization:

Explore and implement best practices for utilizing cloud-native AI platforms, such as Amazon Bedrock and Azure OpenAI, to enhance solution delivery.

Continuous Learning & Innovation:

Stay updated with the latest trends and emerging technologies in the GenAI and AI/ML fields, ensuring our solutions remain cutting-edge.

Requirements:

The ideal candidate will have strong experience in Generative AI technologies, particularly in the areas of RAG, document chunking, and vector database management. They will be able to quickly adapt to evolving AI frameworks and leverage cloud-native platforms to create efficient, scalable solutions. You will be working in a fast-paced and collaborative environment, where innovation and the ability to learn and grow are key to success.

- 3 to 5 years of overall experience in software development, with 3 years focused on AI/ML.

- Minimum 2 years of experience specifically working with Generative AI (GenAI) technologies.

- Python, PySpark and SQL knowledge is necessary for tasks

- Proven ability to work in a collaborative, fast-paced, and innovative environment.

Technical Skills:

- Generative AI Frameworks & Technologies:

- Expertise in Generative AI frameworks, including prompt engineering, fine-tuning, and few-shot learning.

- Familiarity with frameworks such as T5 (Text-to-Text Transfer Transformation), LangChain, Lang Graph, Open-source tech stalk Ollama, Mistral, DeepSeek.

- Strong knowledge of Retrieval-Augmented Generation (RAG) for combining LLMs with external data retrieval systems.

Data Management:

- Experience in designing chunking strategies for different datasets.

- Expertise in data embedding techniques and experience with vector databases like Pinecone, ChromaDB etc

- Programming & AI/ML Libraries:

- Strong programming skills in Python.

- Experience with AI/ML libraries such as TensorFlow, PyTorch, and Hugging Face Transformers.

Cloud Platforms & Integration:

- Familiarity with cloud services for AI/ML workloads (AWS, Azure).

- Experience with API integration for AI services and building scalable applications.

- Certifications (Optional but Desirable):

- Certification in AI/ML (e.g., TensorFlow, AWS Certified Machine Learning Specialty).

- Certification or coursework in Generative AI or related technologies.

Budget: 35 LPA to 45 LPA

Work schedule is Mon to Fri, 3:30am to 12:30pm IST

Key Responsibilities:

• Design, develop, and deploy computer vision and machine learning models for analyzing visual and document-based data.
• Build pipelines that convert unstructured visual inputs into structured and usable information.
• Develop and evaluate models for tasks such as object detection, segmentation, document parsing, and image understanding.
• Apply OCR and related techniques to extract meaningful information from complex documents and imagery.
• Work with large datasets and build efficient training and evaluation pipelines.
• Handle real-world visual datasets that may contain noise, inconsistencies, incomplete information, or varying formats.
• Experiment with different approaches to solve challenging computer vision problems and evaluate tradeoffs between accuracy, performance, and complexity.
• Collaborate with product and engineering teams to integrate machine learning models into scalable production systems.
• Continuously improve model performance, accuracy, and robustness in real-world environments.
• Stay up to date with the latest developments in AI and computer vision and apply relevant techniques where appropriate.
• Actively leverage modern AI tools and frameworks to accelerate experimentation, development, and engineering workflows.

Requirements:

• 5+ years of hands-on experience building and deploying machine learning models, particularly in Computer Vision or document understanding.
• Strong proficiency in Python for machine learning and data processing.
• Hands-on experience with modern ML frameworks such as PyTorch and libraries in the Hugging Face ecosystem.
• Experience with computer vision tooling such as OpenCV.
• Experience with common ML and data science libraries such as scikit-learn, NumPy, and Pandas.
• Experience developing models for tasks such as segmentation, object detection, or document analysis.
• Experience working with large image datasets and building training pipelines.
• Solid understanding of model evaluation, data preprocessing, and performance optimization.
• Strong problem-solving skills and ability to work in a fast-paced product environment.
• Ability to collaborate effectively with cross-functional engineering and product teams.
• The candidate should be based in India
• Willing to work remotely full-time
• Work schedule is Mon to Fri, 3:30am to 12:30pm IST

Preferred Qualifications:

• Experience with TensorFlow or other deep learning frameworks.
• Experience working with OCR pipelines or document analysis systems.
• Experience deploying machine learning models in production environments.
• Experience with containerized deployments such as Docker or Kubernetes.
• Experience working with complex technical documents, diagrams, or structured visual data.
• Familiarity with spatial or geometry-related data problems.
• Experience with libraries such as Detectron2, MMDetection, or similar.
• Familiarity with frameworks used to integrate modern AI models into applications (e.g., LangChain or similar tooling).
• Contributions to open-source ML or computer vision projects are a plus.

Additional Information:

• The problems we work on involve complex visual and document-based data, so we value engineers who enjoy tackling challenging technical problems and experimenting with different approaches to reach practical solutions.
• Candidates are required to include links to relevant projects, GitHub repositories, research work, or examples of machine learning systems they have built.

Benefits:

• Flexible remote work opportunities with career development opportunities
• Engagement with a supportive and collaborative global team
• Competitive market based salary

Job Title: Software Development - Team Lead

Location: Mohali (Phase 8B)

Company: 75WAY Technologies Pvt. Ltd.

Experience: 4+ Years

We are looking for an experienced Software Development Team Lead to manage a team of developers, oversee project execution, and actively participate in client meetings and requirement discussions. The ideal candidate should have strong technical expertise in MERN / MEAN / AIML technologies, along with proven leadership and communication skills to ensure successful delivery of software projects and high client satisfaction.

Responsibilities

• Lead and manage the software development team to deliver high-quality solutions
• Conduct client meetings, requirement gathering, and technical discussions
• Assign tasks, monitor progress, and ensure timely project delivery
• Provide technical guidance and mentorship to developers
• Coordinate between clients and internal teams to resolve issues
• Ensure adherence to coding standards, timelines, and quality processes
• Handle project planning, task allocation, and performance monitoring
• Maintain regular communication with clients regarding project status
• Identify risks and implement solutions to ensure smooth delivery

What You’ll Be Doing:

• Design and develop advanced AI/ML models to solve complex business problems
• Work closely with cross-functional teams including data engineers and domain experts
• Perform exploratory data analysis, data cleaning, and model development
• Translate business challenges into data-driven solutions and actionable insights
• Drive innovation in advanced analytics and AI/ML capabilities
• Communicate model insights effectively to both technical and non-technical stakeholders

What We’re Looking For:

• 5+ years of experience in AI/ML model development
• Strong foundation in mathematics, probability, and statistics
• Proficiency in Python and exposure to Azure Machine Learning / Databricks
• Experience with supervised & unsupervised learning techniques
• Domain exposure to Energy / Oil & Gas value chain (preferred)
• Strong problem-solving, stakeholder management, and communication skills

JOB DETAILS:

- Job Title: Lead I - Data Science - Python, Machine Learning, Spark 

- Industry: Global Digital Transformation Solutions Provider

- Experience: 5-10 years

- Job Location: Pune

- CTC Range: Best in Industry

JD for Data Scientist

Hands-on experience with data analysis tools:

Proficient in using tools such as Python and R for data manipulation, querying, and analysis.

Skilled in utilizing libraries like Pandas, NumPy, and Scikit-Learn to perform in-depth data analysis and modeling.

Skilled in machine learning and predictive analytics:

Expertise in building, training, and deploying machine learning models using frameworks such as TensorFlow and PyTorch.

Capable of performing tasks like regression, classification, clustering, and recommendation, leading to data-driven predictions and insights.

Expertise in big data technologies:

Proficient in handling large datasets using big data tools such as Spark.

Skilled in employing distributed computing and parallel processing techniques to ensure efficient data processing, storage, and analysis, enabling enterprise-level solutions and informed decision-making

Skills: Python, SQL, Machine Learning, and Deep Learning, with mandatory expertise in Generative AI.

Must-Haves

5–9 years of relevant experience in Python, SQL, Machine Learning, and Deep Learning, with mandatory expertise in Generative AI

******

NP - Immediate joiners only

Location-Pune 

The DevOps Engineer will play a critical role in operationalizing artificial intelligence across Bell Techlogix client environments. This role focuses on building and supporting cloud infrastructure, CI/CD pipelines, and automation frameworks that power AI and machine learning workloads. The ideal candidate has experience supporting AI platforms such as Azure AI, Azure Machine Learning, Azure OpenAI, and ServiceNow or conversational AI platforms, and understands the operational requirements of production AI systems, including reliability, scalability, and security. 

Key Responsibilities 

•Design, build, and operate cloud infrastructure and platform services that support AI and machine learning workloads in production, SLA-driven managed services environments 

•Implement CI/CD and MLOps pipelines to enable automated training, testing, deployment, and rollback of AI and ML models 

•Develop and maintain Infrastructure as Code to provision AI-ready environments consistently across dev/test/prod 

•Support AI platform operations including monitoring model health, pipeline execution, compute utilization, and data dependencies 

•Partner with Machine Learning Engineers and Data Engineers to standardize deployment patterns for AI services and LLM-based solutions 

•Enable secure and scalable AI integrations using APIs, messaging, and event-driven architectures 

•Implement observability solutions for AI platforms, including logging, metrics, alerting, and drift detection integrations 

•Troubleshoot AI platform incidents, perform root cause analysis, and implement remediation to improve reliability and automation coverage 

•Apply security best practices for AI environments including secrets management, identity and access controls, network isolation, and policy enforcement 

•Support AI-driven automation use cases across platforms such as Microsoft Copilot, ServiceNow, and conversational AI tools 

•Collaborate with service desk, security, and architecture teams to continuously improve AI service delivery and operational maturity 

Required Qualifications 

•Bachelor’s degree in Computer Science, Engineering, or equivalent practical experience 

•5+ years of experience in DevOps, cloud engineering, or platform operations, with exposure to AI or data workloads 

•Hands-on experience with Microsoft Azure, including compute, networking, storage, and monitoring services 

•Experience building CI/CD pipelines using Azure DevOps, GitHub Actions, or similar tools 

•Working knowledge of Infrastructure as Code (Terraform and/or Bicep/ARM) 

•Scripting experience using PowerShell and/or Python 

•Experience supporting production platforms with incident management, change control, and root cause analysis 

•Understanding of cloud security fundamentals and enterprise governance requirements 

Preferred Qualifications 

•Experience with Azure Machine Learning, Azure AI Services, Azure OpenAI, or MLOps frameworks 

•Exposure to containerization and orchestration technologies (Docker, Kubernetes, AKS) 

•Experience supporting data pipelines or feature stores used by machine learning systems 

•Familiarity with ServiceNow, AI-driven ITSM workflows, or automation platforms 

•Experience with observability tools 

•Knowledge of Responsible AI, data governance, and compliance considerations for AI systems 

•Relevant certifications (Microsoft Azure Administrator, Azure DevOps Engineer, Azure AI Engineer)

The Machine Learning Engineer will play a critical role in supporting Bell Techlogix clients by building, operating, and optimizing AI solutions in a managed services environment. This role focuses on delivering reliable, secure, and scalable AI capabilities across Microsoft AI platforms, Kore.ai conversational AI, and ServiceNow, while also supporting broader AI initiatives and the AI Center of Excellence. 

Key Responsibilities 

•Design, deploy, and support machine learning and AI solutions in production, SLA-driven managed services environments 

•Provide operational support for AI platforms including incident response, troubleshooting, and root cause analysis 

•Monitor AI and ML model performance, data quality, and drift; implement retraining and optimization strategies 

•Build and maintain MLOps pipelines supporting model training, validation, deployment, and rollback 

•Develop and support AI workloads using Microsoft Azure AI, Azure Machine Learning, Azure OpenAI, and Copilot extensibility 

•Design, train, and optimize virtual assistants enterprise workflows 

•Implement and support AI capabilities including Predictive Intelligence, Virtual Agent, and AI Search 

•Collaborate with service desk, engineering, security, and platform teams to drive automation and continuous service improvement 

•Act as a technical escalation point for AI-related client issues and enhancement requests 

•Contribute to AI innovation initiatives, proofs of concept, and reusable solution patterns within Bell Techlogix 

Required Qualifications 

•Bachelor’s degree in Computer Science, Data Science, Machine Learning, or equivalent practical experience 

•5+ years of experience in machine learning engineering, AI development, or applied data science 

•Strong proficiency in Python, SQL, and API-based integrations 

•Hands-on experience supporting machine learning models in production environments 

•Experience working in managed services, consulting, or enterprise IT environments 

•Strong understanding of cloud platforms (Microsoft Azure preferred) 

Preferred Qualifications 

•Experience with Azure Machine Learning, Azure AI Services, or Azure OpenAI 

•Hands-on experience with Kore.ai XO Platform or enterprise conversational AI 

•Experience implementing or supporting ServiceNow AI/ML, Predictive Intelligence, or Virtual Agent 

•Familiarity with MLOps, CI/CD pipelines, Infrastructure as Code (Terraform, Bicep, ARM) 

•Knowledge of Responsible AI, data governance, and enterprise security practices 

•Relevant certifications (Microsoft, ServiceNow, Kore.ai) 

Job Title: Software/Hardware Engineer (IIT/NIT)

Location: Bangalore

Website: https://www.zeuron.ai

Experience: 1 Year

CTC: ₹12 LPA

About the Company

Zeuron.ai is a Bangalore-based deep-tech startup founded in 2019, focused on building brain-inspired computing and AI-driven healthcare solutions. The company combines neuroscience, AI, and gaming to create innovative digital therapeutics and neurotechnology platforms for improving brain health, rehabilitation, and overall well-being.

About the Role

We are looking for a highly motivated Software/Hardware Engineer from premier institutes (IIT/NIT) with strong fundamentals and a passion for building scalable and efficient systems. This role offers an opportunity to work on cutting-edge technology and solve real-world problems.

Key Responsibilities

Design, develop, and optimize software/hardware solutions

Work on system architecture, debugging, and performance improvements

Collaborate with cross-functional teams (product, design, operations)

Participate in code reviews, testing, and deployment processes

Contribute to innovation and continuous improvement initiatives

Requirements

B.Tech/M.Tech from IITs/NITs (Computer Science, Electronics, Electrical, or related fields)

1 year of experience (internships/project experience considered)

Strong programming skills (C/C++/Python/Java) or hardware fundamentals (embedded systems, VLSI, circuit design)

Good understanding of data structures, algorithms, and system design

Problem-solving mindset with strong analytical skills

Preferred Skills

Experience with embedded systems, IoT, or product development

Knowledge of cloud platforms or system-level programming

Good in Computer vision, Flutter, JavaScript, AI/ML

Your Responsibilities

what you will wake up to solve.

• Process-First AI Strategy: Principal Technical Expert: Act as a hands-on leader and the core technical authority tasked with "futurifying" client businesses through advanced AI. Take full ownership of the AI Engineering squad, transforming ambitious concepts into high-impact, tangible realities.
• Engineering & Intelligent Deployment: Execute the full-lifecycle development of innovative AI/ML solutions, including hands-on design, coding, testing, and deployment of robust, scalable systems that prioritize technical excellence and business relevance.
• Scalability & Architectural Optimization: Directly build and optimize high-performance AI architectures and core system components to ensure solutions are reliable, production-ready, and optimized for long-term operational success.
• Impact-Driven Technical Expertise: Deliver intelligent client outcomes through direct technical contribution, maintaining an "Always Beta" mindset and a relentless focus on solving complex engineering challenges.
• Leadership through Action: Lead by example rather than control, coaching and mentoring a high-performing squad of "happier Do-ers" to foster a vibrant culture of continuous innovation and technical excellence.
• Strategic Integration & Collaboration: Partner across internal teams to translate chaotic business challenges into precise technical requirements, ensuring seamless solution integration and adoption for global clients.
• The "Agentic" Shift: You will lead the transition from simple predictive models to Agentic Workflows. You will build systems where AI agents can plan, reason, and execute complex tasks autonomously to solve intricate business problems.
• Talent & Culture: You will mentor a high-performance squad of AI Engineers and Data Scientists. You will teach them to look beyond the algorithm and understand the business outcome.

Functional Skills

Scaling Intelligent Workforce through Delivery Excellence

• Deep Technical Acumen: Operates at the cutting edge of AI, applying advanced technical knowledge to engineer and implement groundbreaking solutions, and guide the squad in developing future capabilities.
• Client Advocacy & Revenue Growth: Skill in cultivating and maintaining trusted client partnerships. Drives strategic engagement that results in repeat business and expanded client portfolios within the region.
• Contract & Risk Governance: High proficiency in reviewing and managing complex project agreements (SoW), mitigating delivery risks, and navigating commercial negotiations to safeguard BU profitability.
• Structured Problem-Solving: Simplifies chaotic technical challenges for the squad by breaking them into solvable chunks using first-principles thinking.
• Squad Delivery Ownership: Follows through on the squad's solution execution—owning technical outcomes from ideation to deployment with rigor, precision, and pride, ensuring tangible, real-world business value.

Technical Oversight & Execution Charter

• Technical Troubleshooting & Crisis Resolution: Actively manages technical roadblocks within the squad, personally intervening to troubleshoot ML or MLOps constraints. You ensure the protection of sprint timelines and the guaranteed performance of deployed models through hands-on problem-solving.
• Cloud-Native Technical Command: Maintains deep, functional knowledge of modern AI system design (e.g., RAG Frameworks, Agentic Workflows, and Inference Optimization) across GCP and AWS. You hold the responsibility to validate squad-level technical roadmaps, ensuring they are technically feasible and production-hardened.
• End-to-End Project Management: Expertly manage all aspects of a project, including scope, budget, timelines, and stakeholder communication. Accountable for the entire delivery, not just the technical parts.
• Talent Strategy & Mentorship: Drive the hiring and development of specialized talent. You will be responsible for defining and optimizing effective team structures while proactively fostering an environment that champions creative problem-solving and technical agility.

Tech Superpowers

• Deep AI Engineering Mastery & Guidance: Possesses profound, hands-on expertise in engineering, optimizing, and deploying foundational models, custom AI solutions, and complex multi-modal systems. You'll also guide your squad in understanding model architectures, training methodologies, and ethical AI development from the ground up, ensuring their collective proficiency.
• Intelligent Systems Architecture & Oversight: You'll directly contribute to and oversee the coding and implementation of robust, scalable, and production-grade AI platforms and MLOps components for your squad's projects. You'll translate abstract technical requirements into high-performance, maintainable AI system designs, always considering reliability, security, and future extensibility across the squad's work.
• Cloud-Native AI capability: More than cloud-certified, you are deeply cloud-capable in applied AI engineering. You proficiently leverage and guide your team in utilizing leading cloud AI/ML ecosystems to build, deploy, and manage AI solutions.
• Technical Integrity & Ethical Governance: Establishes and audits mandatory technical quality benchmarks, ensuring strict adherence to rigorous policies regarding model validation, automated testing coverage, and ethical governance.

Experience & Relevance

• A value-driven AI/ML Engineering Manager with 8+ years of experience in building and scaling end-to-end AI engineering and solution delivery.
• Leadership Track Record: Proven track record as a hands-on builder, and lead, contributing to the design, development, and deployment of complex, enterprise-grade AI/ML platforms and solutions. Expert in leveraging Google Cloud's AI/ML ecosystem (Vertex AI, BigQuery ML, GKE for MLOps) to deliver highly performant, scalable, and impactful AI transformations.
• Delivery & Advisory Record: Experience in building and optimizing intelligent systems and personally driving the technical execution from conception to scalable deployment.
• Applied AI & Domain Expertise: Hands-On AI Deployment: Extensive hands-on experience deploying AI-powered workflows, copilots, and automation solutions in production environments.
• Client-Facing Lead: Demonstrated hands-on experience as an AI/ML Product Manager, Data Science Manager, or Technical Architect in client-facing capacities. This involves directly building, implementing, and advising on complex AI solutions, consistently acting as the trusted technical authority for strategic clients.

Bonus Points (you will thrive if you have)

• Founder’s Energy: Bias for action, thrive in ambiguity, relentless focus on outcomes.
• Low-Code/No-Code Fluency: Experience with AI integrations via Power Platform or similar.
• AI Copilots & Extensions: Built plugins, copilots, or agentic automation frameworks.
• Thought Leadership DNA: Industry content creation, technical blogs, public speaking.
• Ethical Compass: Strong commitment to responsible AI practices.
• Engineer at Heart: Background in product development or engineering before moving into architecture.

Your Responsibilities

what you will wake up to solve.

• Process-First AI Strategy: Principal Technical Expert: Act as a hands-on leader and the core technical authority tasked with "futurifying" client businesses through advanced AI. Take full ownership of the AI Engineering squad, transforming ambitious concepts into high-impact, tangible realities.
• Engineering & Intelligent Deployment: Execute the full-lifecycle development of innovative AI/ML solutions, including hands-on design, coding, testing, and deployment of robust, scalable systems that prioritize technical excellence and business relevance.
• Scalability & Architectural Optimization: Directly build and optimize high-performance AI architectures and core system components to ensure solutions are reliable, production-ready, and optimized for long-term operational success.
• Impact-Driven Technical Expertise: Deliver intelligent client outcomes through direct technical contribution, maintaining an "Always Beta" mindset and a relentless focus on solving complex engineering challenges.
• Leadership through Action: Lead by example rather than control, coaching and mentoring a high-performing squad of "happier Do-ers" to foster a vibrant culture of continuous innovation and technical excellence.
• Strategic Integration & Collaboration: Partner across internal teams to translate chaotic business challenges into precise technical requirements, ensuring seamless solution integration and adoption for global clients.
• The "Agentic" Shift: You will lead the transition from simple predictive models to Agentic Workflows. You will build systems where AI agents can plan, reason, and execute complex tasks autonomously to solve intricate business problems.
• Talent & Culture: You will mentor a high-performance squad of AI Engineers and Data Scientists. You will teach them to look beyond the algorithm and understand the business outcome.

Functional Skills

1. Scaling Intelligent Workforce through Delivery Excellence

• Deep Technical Acumen: Operates at the cutting edge of AI, applying advanced technical knowledge to engineer and implement groundbreaking solutions, and guide the squad in developing future capabilities.
• Client Advocacy & Revenue Growth: Skill in cultivating and maintaining trusted client partnerships. Drives strategic engagement that results in repeat business and expanded client portfolios within the region.
• Contract & Risk Governance: High proficiency in reviewing and managing complex project agreements (SoW), mitigating delivery risks, and navigating commercial negotiations to safeguard BU profitability.
• Structured Problem-Solving: Simplifies chaotic technical challenges for the squad by breaking them into solvable chunks using first-principles thinking.
• Squad Delivery Ownership: Follows through on the squad's solution execution—owning technical outcomes from ideation to deployment with rigor, precision, and pride, ensuring tangible, real-world business value.

2. Technical Oversight & Execution Charter

• Technical Troubleshooting & Crisis Resolution: Actively manages technical roadblocks within the squad, personally intervening to troubleshoot ML or MLOps constraints. You ensure the protection of sprint timelines and the guaranteed performance of deployed models through hands-on problem-solving.
• Cloud-Native Technical Command: Maintains deep, functional knowledge of modern AI system design (e.g., RAG Frameworks, Agentic Workflows, and Inference Optimization) across GCP and AWS. You hold the responsibility to validate squad-level technical roadmaps, ensuring they are technically feasible and production-hardened.
• End-to-End Project Management: Expertly manage all aspects of a project, including scope, budget, timelines, and stakeholder communication. Accountable for the entire delivery, not just the technical parts.
• Talent Strategy & Mentorship: Drive the hiring and development of specialized talent. You will be responsible for defining and optimizing effective team structures while proactively fostering an environment that champions creative problem-solving and technical agility.

Tech Superpowers

• Deep AI Engineering Mastery & Guidance: Possesses profound, hands-on expertise in engineering, optimizing, and deploying foundational models, custom AI solutions, and complex multi-modal systems. You'll also guide your squad in understanding model architectures, training methodologies, and ethical AI development from the ground up, ensuring their collective proficiency.
• Intelligent Systems Architecture & Oversight: You'll directly contribute to and oversee the coding and implementation of robust, scalable, and production-grade AI platforms and MLOps components for your squad's projects. You'll translate abstract technical requirements into high-performance, maintainable AI system designs, always considering reliability, security, and future extensibility across the squad's work.
• Cloud-Native AI capability: More than cloud-certified, you are deeply cloud-capable in applied AI engineering. You proficiently leverage and guide your team in utilizing leading cloud AI/ML ecosystems to build, deploy, and manage AI solutions.
• Technical Integrity & Ethical Governance: Establishes and audits mandatory technical quality benchmarks, ensuring strict adherence to rigorous policies regarding model validation, automated testing coverage, and ethical governance.

Experience & Relevance

• A value-driven AI/ML Engineering Manager with 8+ years of experience in building and scaling end-to-end AI engineering and solution delivery.
• Leadership Track Record: Proven track record as a hands-on builder, and lead, contributing to the design, development, and deployment of complex, enterprise-grade AI/ML platforms and solutions. Expert in leveraging Google Cloud's AI/ML ecosystem (Vertex AI, BigQuery ML, GKE for MLOps) to deliver highly performant, scalable, and impactful AI transformations.
• Delivery & Advisory Record: Experience in building and optimizing intelligent systems and personally driving the technical execution from conception to scalable deployment.
• Applied AI & Domain Expertise: Hands-On AI Deployment: Extensive hands-on experience deploying AI-powered workflows, copilots, and automation solutions in production environments.
• Client-Facing Lead: Demonstrated hands-on experience as an AI/ML Product Manager, Data Science Manager, or Technical Architect in client-facing capacities. This involves directly building, implementing, and advising on complex AI solutions, consistently acting as the trusted technical authority for strategic clients.

Bonus Points (you will thrive if you have)

• Founder’s Energy: Bias for action, thrive in ambiguity, relentless focus on outcomes.
• Low-Code/No-Code Fluency: Experience with AI integrations via Power Platform or similar.
• AI Copilots & Extensions: Built plugins, copilots, or agentic automation frameworks.
• Thought Leadership DNA: Industry content creation, technical blogs, public speaking.
• Ethical Compass: Strong commitment to responsible AI practices.
• Engineer at Heart: Background in product development or engineering before moving into architecture.

Why you’ll love being a ‘Searcian’

NOT your ‘usual’ management consultancy; we ‘solve differently’.

• We are happier. No really happier’: A vibrant, inclusive, and supportive work environment. We even have a dedicated role for ‘Better Living’.
• The Company You Keep (Says Everything): solvers. engineers. tinkerers. improvers. futurists operating across 12 countries.
• No room for CAVEers (Constantly Against Virtually Everything people). Instead, we make room for a meditation room in our offices.
• No bloat: 27 people meeting with 23 clueless people. Not happening here. We also don't do the meetings to plan for pre-meetings.
• No bureaucracy. Zero entropy. Real decision-making velocity: We’re large enough to solve the world’s most complex business challenges, yet small and agile enough to value individual humans. With us, you’re a name, not an employee ID number lost in a sea of 37,000 people where it takes a year just to decide ‘who will decide’.
• Ideas over Hierarchy: We reject HiPPOs (Highest Paid Person’s Opinion). The most well-reasoned ideas win - regardless of whose name is on them. That dangerous phrase, "We’ve always done it this way," dies here.
• Own-the-outcome: The buck stops with you. Doesn’t matter if you are an intern. (Psst: A ‘real intern’ actually drafted this JD.)
• Expert ‘wholesome generalists’, Not ‘one-nut-tighteners’. At Searce, you see the whole picture — how the car is designed, built, and driven — not just how to tighten the third nut on a red 1962 Ford Falcon owned by Vinny’s cousin. Real impact comes from knowing why that nut matters to the person behind the wheel.
• You ‘do stuff’ that matters. Not just “follow up on the deck we shared.”
• Gain more years in your Searce-perience: We operate at a 3.65x experience velocity—yes, we measured it. (and charted it to the scale too)

Join the ‘real solvers’

ready to futurify?

If you are excited by the possibilities of what an AI-native engineering-led, modern tech consultancy can do to futurify businesses, apply here and experience the ‘Art of the possible’. Don’t Just Send a Resume. Send a Statement.

Title: AI Solutions Architect

Location: Gurgaon

Experience: 2-6 years

Type: Full-Time

About the company:

InteligenAI is a fast growing, profitable AI product studio with a global clientele.

We design and deliver enterprise-grade, custom AI solutions that solve real problems - going far beyond makeshift PoCs and over-promising demos.

We’re building one of the most trusted AI services companies in the world - and are looking for a driven, entrepreneurial person to help us get there. Our work spans Agentic AI architectures, document digitization pipelines, retrieval-augmented generation (RAG) systems, and SFT + RLHF workflows - all built in-house so we can move fast, think deep and deliver with confidence.

If you are looking for meaningful work, high ownership and the freedom to push boundaries, you will feel right at home here.

About the role:

We are looking for a hands-on AI engineer to lead AI solution delivery across our client engagements. This role blends technical leadership with solution architecture and a strong product mindset. You will be at the frontline of AI solution delivery, where you will drive the full product lifecycle from understanding business objectives, designing technical approaches, building POCs to delivering production-grade AI systems.

This is not a backseat, “wait for instructions” role. You will work directly with founders, clients, and our growing AI team to shape solutions that make an impact. This role is ideal for someone with an entrepreneurial mindset, a desire to learn and grow constantly and someone who enjoys their work thoroughly. You will be handling multiple responsibilities simultaneously where you will be challenged every day. If you are looking for a 9-to-5 role, this may not be the right fit.

Key responsibilities:

·      Understand business problems, translate them into solution architectures and lead end-to-end AI solution delivery

·      Design and deliver production-grade ML/GenAI systems tailored to real-world use cases

·      Collaborate with clients to identify needs, present solutions and guide implementation

·      Act as a thought partner to the founder and contribute to strategic decisions

·      Lead and mentor a growing AI/Tech team

·      Collaborate with product and design teams to ship AI-driven features that solve real user problems

·      Continuously explore and experiment with cutting-edge GenAI tools, technologies and frameworks

Must have skills:

·      2+ years of hands-on experience building AI/ML solutions across domains

·      Proven ability to understand business workflows and design relevant AI solutions

·      Strong knowledge of GenAI and experience building scalable applications using LLMs, prompt engineering and embedding models

·      Proficient in Python and familiar with libraries/frameworks such as LangChain, Hugging Face Transformers, OpenAI APIs, Pinecone/FAISS

·      Solid understanding of data pipelines, data analytics and ability to take solutions from prototype to production

·      Self-starter mindset- ability to independently manage projects, make decisions and deliver outcomes from day 1

·      Excellent communication and problem-solving skills

Good to have:

·      Open-source contributions or personal GenAI projects

·      Experience working in startups or fast-paced, tech-first organizations

·      Experience with MLOps tools

·      Entrepreneurial experience

🔹 Role: Python Engineer – Python & MLOps

📍 Location: Bellandur, Bangalore

🕐 Work Timings: 01:30 PM – 10:30 PM

🏢 Work Mode: Monday (WFH), Tuesday–Friday (WFO)

📅 Experience: 8-12 Years (Ideal: 8-10 Years)

🔹 Role Overview

This role focuses on building and maintaining a production-grade AI/ML platform. You will work on scalable Python systems, MLOps pipelines, APIs, and CI/CD workflows in an enterprise environment.

🔹 Key Responsibilities

✔ Develop production-grade Python applications using OOP principles

✔ Build and enhance MLOps pipelines (training, validation, deployment)

✔ Design and optimize REST APIs with OpenAI/Swagger

✔ Implement async programming for high-performance systems

✔ Work on CI/CD pipelines (Azure Pipelines / GitHub Actions)

✔ Ensure clean, testable, and maintainable code (PyTest, TDD)

🔹 Required Skills

✔ Strong Python (OOP, modular design)

✔ MLOps & CI/CD pipeline experience

✔ REST API development

✔ Async programming (async/await, concurrency)

✔ Pandas / Polars & Scikit-learn

✔ JSON Schema–driven development

✔ Testing using PyTest

🔹 Nice to Have

➕ Azure ML SDK

➕ Pydantic

➕ Azure Cosmos DB

➕ Experience with large enterprise platforms

Job Title: Lead Data Architect (AI & Cloud)

Company: Risosu Consulting

About the Role

Risosu Consulting is hiring a Lead Data Architect / Crew Manager for one of our global clients in the Cloud, Data & AI space. This role focuses on designing scalable data architectures and driving AI-led transformation across modern cloud platforms.

Key Responsibilities

• Design data strategies, architectures, and scalable cloud solutions
• Build and optimize data pipelines, data lakes, and warehouses
• Collaborate with cross-functional teams to enable AI/ML use cases
• Lead client engagements and translate business needs into data solutions
• Mentor and manage a team of consultants as a Crew Manager

Requirements

• 5+ years of experience in Data Architecture / Engineering
• Strong expertise in cloud platforms (GCP/AWS/Azure)
• Experience with data modeling, ETL, and data governance
• Exposure to tools like BigQuery, dbt, Airbyte, or Power BI
• Strong communication skills and stakeholder management

Why Join via Risosu?

• Opportunity to work on high-impact global projects
• Fast-growing, entrepreneurial environment
• Clear growth path with learning & certification support
• Work with cutting-edge Cloud, Data & AI technologies

If you’re passionate about building scalable data systems and leading teams, let’s connect.

Job Title: Data Architect – AI/ML (Travel Domain)

We’re hiring a Data Architect to build and scale data systems powering AI/ML solutions in the travel domain. In this role, you will design data lakes/warehouses, create robust ETL pipelines, and enable real-time analytics for flight, hotel, and booking platforms. You will work closely with data scientists and engineering teams to support personalization, pricing, and recommendation engines.

Key Requirements:

• 5+ years in data architecture / engineering
• Strong experience with AWS/GCP/Azure and big data tools
• Expertise in ETL, data modeling, and pipeline design
• Good understanding of ML data workflows
• Experience in travel, e-commerce, or high-volume platforms is a plus

If you’re passionate about building scalable data ecosystems and driving AI-led innovation, we’d love to connect.

Job Description – AI Tech Lead

Location: Bangaluru

Experience: 10+ Years

Function: AI Center of Excellence (CoE)

Reporting To: Senior Vice President – CX / Head of AI CoE

We are seeking two highly experienced AI Tech Leads (AVP/DGM level) to drive the architecture, development, and delivery of large‑scale AI solutions spanning Predictive AI, GenAI, and Agentic AI across BPM, IT Services, Digital, Data Engineering, and Enterprise Transformation programs.

The role demands strong technical leadership, solution design capabilities, hands‑on execution ownership, and the ability to lead multi‑disciplinary teams to deliver scalable, production‑grade AI systems.

2. Key Responsibilities

A. Solution Architecture & Strategy

• Lead end‑to‑end solution architecture across Predictive AI, GenAI, Agentic AI, and enterprise data ecosystems.
• Partner with business and technology teams to define AI strategy, technical roadmaps, and implementation frameworks.
• Translate business goals into scalable AI architectures leveraging microservices, distributed systems, and modern AI toolchains.
• Own architectural decisions on model design, data pipelines, deployment frameworks, MLOps stack, and scaling strategies.

B. Project Delivery & Execution Leadership

• Drive the complete AI project lifecycle: Requirement Analysis → Architecture → Model Development → Engineering → Deployment → Monitoring.
• Lead AI engineering teams in developing production‑grade ML/GenAI/Agentic solutions with high reliability and performance.
• Establish and enforce engineering best practices, coding standards, DevOps/MLOps processes, and quality controls.
• Manage multiple concurrent AI initiatives with strong governance, risk mitigation, and stakeholder communication.

C. Technical Hands-on Expertise

• Architect and build complex AI systems involving:
• Large Language Models (LLMs) & GenAI apps
• Agentic workflows and autonomous task orchestration
• Predictive modeling, forecasting, optimization, and statistical modeling
• Knowledge graphs, vector databases, embeddings
• Data engineering pipelines (ETL/ELT) and cloud-native architectures
• Drive model evaluation, experimentation, benchmarking, A/B testing, and continuous improvements.

D. Team Leadership & Mentoring

• Lead and mentor a team of AI engineers, data scientists, MLOps engineers and developers.
• Build internal capabilities by establishing training, code reviews, reusable accelerators, and technical playbooks.
• Actively collaborate with product managers, data engineering teams, CX strategy teams, and domain SMEs.

E. Stakeholder & Client Management

• Act as a technology partner during client discussions, proposals, RFP responses, and solution demonstrations.
• Communicate complex AI concepts to CXOs, business leaders, and non-technical stakeholders seamlessly.
• Support pre-sales with solutioning, effort estimation, and technical presentations.

3. A. Technical Skills

• Strong proficiency in Python, cloud platforms (Azure/AWS/GCP), and AI frameworks (TensorFlow, PyTorch, LangChain, LlamaIndex).
• Hands-on experience building applications using:
• LLMs, RAG, fine‑tuning, prompt engineering
• Autonomous AI agents & multi-agent systems
• Predictive ML models (Regression, Classification, Clustering, NLP, CV)
• Expertise in microservices architecture, API design, scalable deployments.
• Strong command over SDLC, Agile methodologies, CI/CD, DevOps & MLOps.
• Experience with data engineering tools: Spark, Databricks, Airflow, Kafka, SQL/NoSQL, and modern data lakehouse platforms.

B. Functional & Domain Skills

• Experience working in BPM, Customer Experience, Digital Transformation, IT Services.
• Ability to map AI use cases to business value: workflow optimization, automation, customer experience, operations, and analytics.

C. Leadership & Soft Skills

• Strong team leadership and mentoring experience.
• Excellent communication, client-facing abilities, and stakeholder management skills.
• Strong decision-making, problem-solving, and delivery ownership.

4. Qualifications

• Bachelor’s / Master’s in Computer Science, Engineering, Data Science, or related fields.
• 10–15 years total experience with at least 5+ years leading AI/ML projects.
• Demonstrated success delivering large-scale AI programs in enterprise environments.
• Certifications in AI/ML, cloud, or architecture (preferred).