50+ Machine Learning (ML) Jobs in India

Job Location 

Bengaluru, Hyderabad or Noida

Job Summary 

Oracle Health is looking for an Applied Scientist 5 to build and productionize advanced AI/ML solutions that power next-generation healthcare platforms. In this senior individual contributor role, you will lead end-to-end applied research and development across areas such as clinical NLP, recommendations, anomaly detection, LLM-based assistants, and predictive modeling—working closely with product, engineering, and clinical experts to deliver measurable impact on patient outcomes and provider efficiency.

Responsibilities 

• Lead the design, development, and deployment of AI/ML models for Oracle Health products (e.g., clinical NLP, triage, risk prediction, workflow automation, recommendations).
• Own end-to-end ML lifecycle: problem formulation, data exploration, feature engineering, modeling, experimentation, evaluation, and productionization.
• Build and optimize models using modern techniques: deep learning, transformers, LLMs, sequence models, gradient boosting, and classical ML where appropriate.
• Design and implement scalable training, inference, and monitoring pipelines in partnership with platform and backend engineering teams.
• Collaborate with product managers, clinicians, and domain experts to define use cases, metrics, and success criteria aligned to clinical and business outcomes.
• Drive experimentation at scale (A/B tests, offline/online evaluation), and translate results into product decisions.
• Work with large, noisy, and heterogeneous healthcare datasets (structured, unstructured text, time-series, logs, and images where relevant) while preserving privacy and compliance.
• Ensure models meet requirements for robustness, fairness, explainability, reliability, and security, especially in clinical workflows.
• Mentor and guide junior scientists and engineers; review designs, code, experiments, and documentation.
• Contribute to the long-term AI/ML roadmap, architecture, tooling, and best practices within Oracle Health and across Oracle AI teams.
• Stay current with research in AI/ML, especially in healthcare and LLMs, and bring relevant advances into production systems.

Required Qualifications 

• 10+ years of experience in applied machine learning, data science, or related roles, with a strong track record of shipping production ML systems.
• PhD in Computer Science, Machine Learning, Statistics, or related field, or MTech/MS with strong applied experience.
• Deep expertise in at least one of: NLP (including transformers/LLMs), time-series modeling, recommendation systems, optimization, or causal inference.
• Strong hands-on skills in Python and ML ecosystems (e.g., PyTorch, TensorFlow/JAX, Hugging Face, scikit-learn, XGBoost/LightGBM).
• Proven experience designing experiments, defining metrics, and evaluating models rigorously in real-world settings.
• Experience building and deploying scalable ML services in production (microservices, REST/gRPC, or batch pipelines) in partnership with software engineering teams.
• Strong understanding of data management and MLOps concepts: feature stores, model versioning, monitoring, drift detection, and CI/CD for ML.
• Ability to translate ambiguous business or clinical problems into well-defined ML formulations and deliver solutions with clear impact.
• Excellent communication skills, with experience influencing cross-functional stakeholders and making clear technical and product recommendations.

Preferred Qualifications 

• Experience with LLMs and generative AI: prompt engineering, fine-tuning, retrieval-augmented generation (RAG), safety/guardrails, and evaluation.
• Background working with healthcare data (EHR/EMR, clinical notes, claims, imaging, device data) or other regulated, high-stakes domains.
• Familiarity with privacy, security, and compliance requirements (HIPAA or similar), de-identification, and data governance.
• Experience with cloud platforms and distributed systems (OCI preferred; AWS/Azure/GCP also relevant), and technologies such as Kubernetes, Docker, Kafka, Spark.
• Contributions to research (publications, patents, open-source projects) in machine learning, NLP, or related fields.
• Experience leading technical strategy, roadmaps, or cross-team AI/ML initiatives.

About Oracle Health 

Oracle Health is transforming healthcare by building secure, intelligent, and scalable cloud-based solutions that help clinicians make better decisions and improve patient outcomes. As an Applied Scientist 5, you will shape the AI/ML foundation of Oracle Health, working on mission-critical problems at the intersection of cloud, data, and healthcare.

Supercharge Your Career as a AI DevOps Engineer at Technoidentity!

At Technoidentity, we're a Data & AI product engineering company with over 15 years of expertise in building durable digital products, intelligent enterprise solutions, and scalable Data & AI platforms. As we continue expanding globally, it's the perfect time to join our team of tech innovators and make a lasting impact.

What’s in it for You?

We are looking for an AI DevOps Engineer with 0–3 years of experience who is passionate about AI, Cloud, DevOps, and Automation. The role involves building, deploying, and managing AI-powered applications, LLM solutions, and cloud-native platforms while ensuring reliability, scalability, security, and observability.

What Will You Be Doing?

• Develop and deploy AI/ML and Generative AI solutions using Python.
• Build applications leveraging LLMs, RAG, and AI agents.
• Create and maintain CI/CD pipelines for AI applications.
• Deploy and manage workloads using Docker and Kubernetes.
• Support cloud platforms (AWS, Azure, or GCP).
• Implement Infrastructure as Code (Terraform) and automation workflows.
• Monitor applications using observability tools such as Prometheus, Grafana, and logging platforms.
• Collaborate with engineering teams to ensure system reliability, performance, and security.
• Contribute to MLOps practices, AI accelerators, and reusable frameworks.

Requirements

What Makes You the Perfect Fit?

• Python programming (mandatory)
• Understanding of Machine Learning, LLMs, Prompt Engineering, and RAG
• Experience with OpenAI, LangChain, LlamaIndex, or Hugging Face
• Docker, Kubernetes, Git, and CI/CD tools
• AWS, Azure, or GCP
• PostgreSQL; MongoDB and Vector Databases are a plus
• Basic knowledge of MLOps, Terraform, and workflow orchestration tools (Airflow/Temporal)
• Familiarity with observability and monitoring tools

Qualifications

• Bachelor's degree in Computer Science, AI, Data Science, IT, or related field
• 0–3 years of experience in AI/ML, Software Engineering, Cloud, DevOps, or related areas

Nice to Have

• Experience with Agentic AI frameworks
• Knowledge of MLOps and AI platform operations
• Exposure to enterprise-grade monitoring, reliability engineering, and security best practices

About Ritually

Ritually is building the definitive process discovery platform for back office work. Our product fuses underutilized system telemetry with computer vision to help large enterprise and scaling mid-market companies deeply understand and reimagine their highest value and most repetitive processes for a world where humans and agents work together. We're based in New York and Denver.

We believe deeply in trust (of our customers and each other), craft, customer obsession, and speed.

You'll be joining an AI-native, fast-moving, and repeat founding team. Ritually's founders previously built and exited a startup (Involvio) to Cisco. The company is funded and working with design partners.

The Role

This is a founding applied-AI role. You'll be building our core data pipeline and intelligence layer with the founding team from 0-1 You'll be tackling our largest technical challenges across technologies.

What You'll Do

• Design and build data pipelines that capture and turn high volumes of system activity into structured, queryable data.
• Turn raw activity streams into processes: sessionize event logs, cluster recurring sequences, and use LLMs to label and summarize what's happening.
• Build the evaluation backbone from scratch: stand up synthetic data generation pipelines that produce labeled scenarios to measure accuracy and catch regressions.
• Own data quality and privacy.
• Partner closely with the founders and the rest of engineering to ship features end to end.

What We're Looking For

• 1-4 years of experience in data engineering, AI/ML engineering, or backend work with a data focus (some of this can be project or research experience).
• Strong in Python and/or TypeScript, comfortable in SQL, and able to build data pipelines you can trust.
• Hands-on experience working with LLMs structured output, prompting, and wrangling non-determinism while keeping behavior reliable.
• A practical sense for evaluation: you know that "it looks right" isn't the same as "it's measurably right."
• Care about data privacy and handling sensitive information responsibly.
• Comfort with ambiguity and a real appetite to own a hard, open-ended problem.

Nice to Have

• Background in process mining, sequence / event-log analysis, or workflow analytics.
• Deeper PostgreSQL: window functions, partitioning, pg_cron, query performance.
• Embeddings and vector search (pgvector) or semantic retrieval.
• Familiarity with cloud infrastructure.
• Any prior early-stage startup experience.
• Degree in computer science or a related field.

ob Title: AIML Engineer

Location: Hyderabad

Experience: 1+ year

Role Overview:

 We are looking for a passionate and skilled AI/ML Engineer to join our dynamic team. In this role, you will play a key part in designing and implementing intelligent systems, including the development of a cutting-edge Sales Supervisor Agent. You will work on projects involving Generative AI, Voice AI, sales performance analysis, and recommendation systems that drive automation and strategic decision-making in sales operations.

Key Responsibilities

1. AI/ML System Development

• Design, train, and deploy AI/ML models to identify patterns in sales behavior and trends.
• Develop intelligent recommendation engines to optimize sales strategies.
• Build real-time dashboards for sales performance monitoring and actionable insights.
• Integrate APIs for seamless interaction with internal and external systems.

2. Programming & Development

• Develop and deploy AI/ML models using Python.
• Work with PyTorch or TensorFlow for deep learning applications.
• Build and maintain backend services using FastAPI or Flask.
• Follow collaborative workflows using Git for version control and team development.

3. AI/ML Expertise

• Apply foundational knowledge of LLMs, Transformers, and Retrieval-Augmented Generation (RAG).
• Use NLP techniques to extract and understand customer insights.
• Manage the end-to-end ML lifecycle, including data preprocessing, model training, hyperparameter tuning, and production deployment.

4. Generative AI & Voice AI

• Experiment with Generative AI models (e.g., GPT, Claude) for tasks such as content creation, email generation, and chat-based assistance.
• Build and integrate AI Voice solutions like speech-to-text, call summarization, and conversational agents using tools such as Whisper, ElevenLabs, or Dialogflow.
• Integrate GenAI and Voice AI capabilities into the Sales Supervisor Agent for automation and decision support.

5. Data Engineering & Analysis

• Write efficient SQL queries for data extraction and transformation.
• Use libraries like Pandas and NumPy for data preprocessing and analysis.
• Create meaningful visualizations to deliver actionable insights.

Preferred Skills

• Hands-on experience in applied ML or pattern recognition projects.
• Knowledge of time series analysis and forecasting techniques.
• Familiarity with vector databases such as Faiss or Pinecone.
• Experience with RESTful APIs and cloud platforms (AWS, Azure).
• Exposure to modern AI dev tools like Cursor AI, Claude Code, Copilot, Gemini, Grok.AI, or Codegiantio.

Qualifications

• B.Tech/B.E. in Computer Science, Data Science, or related fields.
• Strong foundation in AI/ML, data structures, and algorithms.
• 1–3 years of relevant experience in AI/ML engineering or applied machine learning.

Key Personal Attributes

• Strong analytical and problem-solving mindset.
• Quick learner with a passion for emerging AI technologies.
• Effective communicator and collaborative team player.
• Proactive and self-driven approach to work.

About WINIT

WINIT is a market leader in Mobile Sales Force Automation (mSFA) with over 25 years of industry expertise. We enable 600+ enterprises globally to enhance sales performance through automation, AI/ML, and real-time insights. Our next-gen AI-powered platform drives intelligent decision-making, optimized logistics, and compliance tracking. With continuous innovation and 24x7 global support, WINIT is shaping the future of sales using AI, GenAI, and Voice AI technologies.

About the Internship

SkillSecure X is seeking passionate Artificial Intelligence & Machine Learning (AI/ML) Interns who are eager to develop practical skills in machine learning, deep learning, and AI applications. Interns will work on guided projects, gain hands-on experience with real-world datasets, and learn industry-standard AI tools and techniques.

Responsibilities

• Assist in developing AI and Machine Learning models.
• Work with Python and popular ML libraries.
• Prepare, clean, and analyze datasets.
• Perform data preprocessing and model evaluation.
• Build basic predictive and classification models.
• Document project progress and complete weekly assignments.

Required Skills

• Basic knowledge of Python programming.
• Understanding of Machine Learning fundamentals.
• Familiarity with Data Science concepts.
• Knowledge of libraries such as NumPy, Pandas, or Scikit-learn is a plus.
• Strong analytical and problem-solving skills.

Eligibility

• Undergraduate or postgraduate students.
• Recent graduates.
• Students pursuing Computer Science, Artificial Intelligence, Data Science, Information Technology, Engineering, or related disciplines.

Benefits

• Hands-on AI & ML project experience.
• Mentor-guided learning.
• Internship Completion Certificate.
• Letter of Recommendation (based on performance).
• Portfolio-building opportunities.
• Flexible remote internship.

Job Title: Associate AI/ML Engineer

Location: Gurugram, Haryana

Employment Type: Full-Time

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 a growing startup, we are looking for passionate and versatile professionals eager to work on cutting-edge projects in a dynamic environment.

Role Overview

As a Associate AI/ML Engineer at Aaizel Tech, you will lead the design, development, and deployment of advanced Machine Learning models and AI solutions. You will work on projects ranging from predictive analytics and NLP to computer vision and anomaly detection. You will also mentor a team of AI/ML professionals, collaborate with cross-functional teams, and drive innovation by integrating state-of-the-art research with scalable production systems.

Key Responsibilities

1. Model Development & Optimization

Design & Implementation:

• Architect and develop end-to-end ML solutions for applications such as predictive analytics, anomaly detection, computer vision, and NLP.
• Utilize advanced techniques including deep learning (CNNs, RNNs), reinforcement learning, and generative models (GANs) to address complex challenges.

Optimization:

• Fine-tune model parameters using techniques such as hyperparameter tuning (Grid Search, Bayesian Optimization, Neural Architecture Search).
• Optimize models for both accuracy and inference speed to meet real-time processing requirements.

2. Advanced Data Engineering & Integration

Data Pipeline Development:

• Build robust ETL pipelines using libraries like Pandas, NumPy, and PySpark to process large-scale datasets from satellite imagery, IoT sensors, and real-time streams.
• Integrate data from diverse sources (APIs, databases, big data platforms like Hadoop and Apache Kafka) to support real-time analytics.

Data Quality & Preprocessing:

• Implement data cleansing, feature engineering, and transformation pipelines to ensure high-quality inputs for ML models.

3. Research & Innovation

Algorithm Research:

• Conduct research on state-of-the-art ML techniques including Transfer Learning, Transformer models, and AutoML to enhance model performance.
• Innovate new algorithms for specialized tasks such as geospatial analysis, environmental modeling, or cybersecurity threat detection.

Prototyping & Experimentation:

• Develop proof-of-concept models and prototypes to validate new approaches before production deployment.

4. Deployment, MLOps & Performance Monitoring

Model Deployment:

• Deploy models using containerization (Docker) and orchestration tools (Kubernetes) to ensure scalable and efficient production environments.
• Work with cloud platforms (AWS, Azure, GCP) and model serving solutions (TensorFlow Serving, ONNX, TorchServe) for high-throughput inference.

MLOps & Lifecycle Management:

• Implement CI/CD pipelines for ML models, ensuring seamless updates and versioning.
• Develop monitoring dashboards (using Prometheus, Grafana) to track model performance and trigger retraining based on real-time feedback.

5. Collaboration & Leadership

Cross-Functional Teamwork:

• Collaborate closely with data engineers, software developers, domain experts, and product managers to integrate AI solutions into end-to-end products.

Mentorship & Code Quality:

• Provide technical leadership and mentorship to junior AI/ML engineers, ensuring adherence to coding standards and best practices.
• Participate in code reviews, maintain detailed documentation, and foster a culture of continuous learning.

Recommended Technology Stack

Backend Framework:

• Python (Django/FastAPI): Ideal for API integration, leveraging Python’s rich AI/ML ecosystem.

AI/ML Frameworks:

• PyTorch + Hugging Face Transformers + scikit-learn: For flexibility in research, multilingual NLP tasks, and classical ML pipelines.

Data Engineering:

• Apache Kafka + Apache Spark + Apache NiFi: To handle both real-time data streaming and batch processing.

Database & Storage:

• PostgreSQL with TimescaleDB extension: For structured and time-series data storage.

DevOps & Monitoring:

• Docker, Kubernetes, GitLab CI/CD, Prometheus/Grafana: For containerized deployments, continuous integration, and comprehensive monitoring.

Media Processing:

• OpenCV, FFmpeg, Tesseract OCR, Wav2Vec2: To support image, video, and speech-to-text processing where needed.

Required Skills & Qualifications

Technical Expertise:

• Experience:
• 5+ years in Machine Learning, AI research, or a related field with a proven track record of delivering production-level AI solutions.
• Programming & Frameworks:
• Expertise in Python and hands-on experience with frameworks like PyTorch, TensorFlow, and scikit-learn.
• Experience with Hugging Face Transformers for NLP applications.
• Data Engineering:
• Proficiency in building data pipelines using Pandas, NumPy, PySpark, and integrating data from diverse sources.
• Familiarity with big data platforms and real-time data processing frameworks.
• Model Deployment & MLOps:
• Hands-on experience with containerization (Docker), orchestration (Kubernetes), and CI/CD pipelines for ML models.
• Experience with cloud deployment and model serving solutions.
• Research & Innovation:
• Demonstrated ability to apply advanced ML techniques (deep learning, transfer learning, reinforcement learning) to solve real-world problems.
• Testing & Optimization:
• Strong background in model evaluation, hyperparameter tuning, and performance optimization.

Soft Skills:

• Exceptional problem-solving and analytical abilities.
• Strong communication skills, with the ability to present complex technical concepts to diverse stakeholders.
• Leadership and mentoring experience, with a collaborative approach to working in cross-functional teams.
• Ability to thrive in a fast-paced, dynamic environment and drive continuous innovation.

Educational Background:

• Bachelor’s or Master’s degree in Computer Science, Data Science, Machine Learning, or a related field from a reputed institution.

What We Offer

• Innovative Projects: Engage in cutting-edge AI/ML projects that influence product strategy and technological innovation.
• Professional Growth: Opportunities for continuous learning, mentorship, and career advancement.
• Collaborative Culture: Work within a diverse team of experts passionate about pushing the boundaries of technology.
• Impactful Work: Play a key role in shaping AI-driven solutions and driving real-world impact.

Role Overview

We are looking for an AI Security Engineer with a strong foundation in both Artificial Intelligence and Cyber Security. This role focuses on building secure AI systems,

protecting LLM-based applications, and embedding security across the entire AI lifecycle, from data to deployment.

Key Highlights

• Work hands-on with LLMs and Generative AI use cases with a strong security focus
• Design and secure RAG-based intelligent applications
• Implement secure vector databases and semantic search systems
• Drive AI security across MLOps and DevSecOps pipelines
• Opportunity to build and scale secure AI solutions in production environments

Required Skills & Qualifications:

• 5+ years of experience in Python development
• Strong experience with frameworks like Django, Flask, or FastAPI
• Hands-on expertise in AWS cloud services (EC2, Lambda, S3, RDS, ECS, etc.)
• Experience with Hugging Face, LangChain, Transformers
• Strong understanding of microservices and distributed systems
• Experience with relational and NoSQL databases (PostgreSQL, MySQL, MongoDB), vector databases
• Proficiency with version control practices
• Experience with CI/CD pipelines and automation tools

Must-Have Skills(AI- specific)

• Strong proficiency in Python
• Hands-on experience with ML, DL & Large Language Models (LLMs),
• Experience with RAG architecture and secure data pipelines
• Strong background in Cyber Security / Information Security domain
• Understanding of application security, cloud security, and network security fundamentals

Security-Specific Expertise

Strong knowledge of:

• OWASP Top 10 / API Security Top 10, Encryption (data at rest & in transit)
• Secure coding practices, Vulnerability Assessment & Penetration Testing (VAPT)
• Authentication & Authorization (OAuth2, JWT, SSO)
• Prompt Injection Attacks, Identity & Access Management (IAM)
• Data Leakage & Sensitive Data Exposure
• Model Poisoning / Adversarial Attacks
• Threat Modeling (STRIDE / MITRE ATT&CK)
• Secrets management (Vault, KMS, etc.)

Responsibilities

• Design and implement secure AI/ML architectures
• Perform AI security assessments, threat modeling, and VAPT
• Build and enforce LLM guardrails and security controls
• Collaborate with engineering teams to embed security-by-design principles
• Monitor and respond to AI-specific and cyber security threats
• Ensure compliance, governance, and risk management for AI systems

Company Overview:

Euphoric Thought Technologies is a cutting-edge technology firm dedicated to solving complex spatial and computational challenges through advanced artificial intelligence. We operate at the intersection of geospatial intelligence and machine learning, building scalable platforms that process massive datasets to provide actionable insights. Our culture is rooted in engineering excellence, where we empower our teams to push the boundaries of Generative AI and deep learning to solve real-world problems for global enterprises.

Role Overview:

As a Technical Lead for AI/ML, you will spearhead the design and implementation of sophisticated machine learning models integrated with geospatial data architectures. You will work closely with cross-functional teams, including data scientists, cloud engineers, and product managers, to translate complex business requirements into high-performance AI solutions. Your work will directly influence the scalability and intelligence of our core platforms, ensuring that our technical infrastructure remains at the forefront of the industry while delivering measurable value to our clients.

Key Responsibilities:

- Architect and deploy end-to-end AI/ML pipelines that integrate seamlessly with GIS and geospatial data streams to enhance predictive accuracy.

- Lead the development and fine-tuning of Large Language Models (LLMs) and Generative AI applications to automate complex analytical workflows.

- Design robust CI/CD pipelines for machine learning models to ensure rapid, reliable, and automated deployment across cloud environments.

- Mentor junior engineers and foster a culture of technical rigor, code quality, and innovative problem-solving within the AI/ML team.

- Collaborate with stakeholders to define technical roadmaps, ensuring that AI initiatives align with long-term business objectives and scalability requirements.

- Optimize deep learning models using frameworks like TensorFlow and PyTorch to improve inference speed and resource efficiency in production.

Required Skillset:

- Demonstrate deep expertise in building and scaling AI/ML solutions, backed by 6 to 8 years of professional experience in the field.

- Possess advanced proficiency in Python and deep learning frameworks such as PyTorch and TensorFlow, with a proven ability to architect complex models.

- Exhibit strong knowledge of GIS and geospatial data processing, with the ability to integrate spatial intelligence into machine learning workflows.

- Showcase a solid foundation in Cloud Architecture, specifically in designing and managing AI/ML infrastructure on major cloud platforms.

- Demonstrate mastery in DevOps practices, including the implementation of CI/CD pipelines for machine learning models to streamline production cycles.

- Communicate complex technical concepts effectively to both technical and non-technical stakeholders, facilitating seamless cross-departmental collaboration.

- Adapt quickly to a distributed work environment, maintaining high levels of productivity and team engagement across multiple locations.

About Us

We are a fast-growing startup based in Pune, India, specializing in cutting-edge Data Science and Data Engineering solutions. Our team of dedicated professionals is committed to solving complex data challenges for companies worldwide.

Our Culture We foster a vibrant startup culture that values: • Intellectual curiosity • Continuous learning • Positive work environment • Collaborative problem-solving

Role Overview

We are seeking a versatile and proactive Data Scientist to join our dynamic team. The ideal candidate will possess a blend of technical expertise in modern AI/ML technologies, strategic planning, and effective communication skills. This role demands critical thinking, applying data science and problem-solving skills to a wide variety of real-world problems, adaptability to rapidly evolving technologies, and a strong foundation in both traditional and generative AI principles.

Key Responsibilities • Deliver end-to-end data science projects by applying Machine Learning and Deep Learning fundamentals to solve complex problems • Derive actionable insights for a variety of problems, industries, and domains using statistical analysis and advanced data science techniques • Develop high-quality software solutions with Python and other programming languages. Collaborate with developers to understand and improve existing code or create new solutions • Build and deploy production-ready LLM applications using modern frameworks and best practices • Design and implement RAG (Retrieval-Augmented Generation) architectures using vector databases and embedding models • Perform prompt engineering and optimization to maximize LLM performance for specific use cases • Implement agentic AI systems and multi-agent workflows for complex automation tasks • Evaluate and benchmark LLM outputs using appropriate metrics and testing frameworks • Build sophisticated data pipelines for large-scale data processing using modern orchestration tools • Optimize database performance and create efficient SQL queries • Deploy and monitor ML models in production using MLOps practices and containerization • Practice active listening to understand project requirements and team inputs • Collaborate with clients to translate business requirements into data science solutions • Communicate complex ideas and results clearly to stakeholders through both verbal and written formats • Apply responsible AI principles and ensure ethical considerations in model development • Demonstrate punctuality and a strong sense of ownership in all tasks • Plan strategically and multitask efficiently to meet project deadlines • Employ critical thinking to break down problems and debug effectively • Take initiative and be biased towards action to drive project progress Required Skills Core Programming & ML • Strong Python programming skills with hands-on project experience • Expertise in Machine Learning and Deep Learning algorithms (Random Forests, GBMs, Neural Networks, CNNs, RNNs, Transformers, Ensemble methods) • Proficiency in TensorFlow or PyTorch, along with scikit-learn and pandas • Familiarity with modern ML techniques: Transfer Learning, Few-shot Learning, Self-supervised Learning • Experience with NLP, Computer Vision, or Time Series Analysis Generative AI & LLMs • Hands-on experience with LLM providers (OpenAI, Anthropic Claude, Google Gemini, or open-source models) • Proficiency with GenAI orchestration frameworks (LangChain, LangGraph, LlamaIndex, or DSPy) • Experience building RAG applications with vector databases (Pinecone, Weaviate, Chroma, FAISS) • Strong prompt engineering skills and understanding of prompt optimization techniques • Knowledge of fine-tuning techniques (LoRA, QLoRA) and when to apply them • Understanding of LLM evaluation metrics and benchmarking methodologies • Familiarity with agentic AI architectures and multi-agent systems MLOps & Deployment • Experience with MLOps practices and tools (MLflow, Kubeflow, Weights & Biases) • Proficiency with containerization using Docker and orchestration with Kubernetes • Experience with cloud platforms (AWS, Azure, or GCP) for ML model deployment and monitoring • Understanding of CI/CD pipelines for ML applications • Knowledge of model serving frameworks and API development (FastAPI, Flask, or Django) Data Engineering & Databases • Solid understanding of SQL, including advanced concepts like windowing functions and query optimization • Experience with data pipeline orchestration tools (Airflow, Prefect, or similar) • Familiarity with both SQL and NoSQL databases Soft Skills & Professional Attributes • Strong critical thinking and problem-solving skills • Excellent written and verbal communication abilities • Demonstrated ability to work well in a team and independently • High degree of flexibility and adaptability to rapidly evolving technologies • Understanding of AI safety principles and responsible AI practices

Nice-to-Have • Experience with big data technologies (Spark, Hadoop, Databricks) • Familiarity with BI tools and dashboard creation (Tableau, Power BI, Looker) • Knowledge of graph databases and knowledge graph construction • Experience with real-time streaming data processing • Active participation in data science competitions (Kaggle, DrivenData) • Contributions to open-source AI/ML projects or technical blog • Experience with multimodal AI models (vision-language models, audio processing) • Published research papers or conference presentations

Qualifications • Data Scientist I: 0-2 years of hands-on experience in Data Science projects • Data Scientist II: 2-5 years of hands-on experience in Data Science projects • Bachelor's or Master's degree in Computer Science, Data Science, Statistics, or related technical field • Demonstrated commitment to continuous learning through courses, certifications, or self-study (especially in GenAI and modern ML techniques)

What We Offer • Competitive salary commensurate with experience • Opportunity to work on diverse, cutting-edge AI/ML projects • Collaborative and innovation-driven work environment • Rapid growth and continuous learning opportunities • Exposure to latest AI technologies and industry best practices

Link for application -  https://forms.gle/9GENVfPeXdtgi7Zj7

Senior AI/ML Engineer

Location: Gurugram, Haryana

Employment Type: Full-Time

Experience: 5+ Years

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.

Role Overview

As AI/ML Engineer, you will lead the development, deployment, and optimization of advanced AI systems spanning Generative AI, Large Language Models (LLMs), Agentic AI, Computer Vision, and intelligent automation. You will drive innovation, mentor junior engineers, and build scalable, production-ready AI solutions.

Key Responsibilities

AI Development & Research

• Design and develop end-to-end AI/ML solutions using Machine Learning, Deep Learning, and Generative AI techniques.
•  
• Build solutions involving NLP, Computer Vision, multimodal AI, anomaly detection, and predictive analytics.
•  
• Develop and optimize LLM-based applications, RAG pipelines, and Agentic AI workflows.
•  
• Fine-tune and evaluate foundation models, including LLMs and Vision Language Models (VLMs).
•  
• Research, prototype, and productionize state-of-the-art AI techniques.

Model Optimization & Deployment

• Optimize models for performance, scalability, latency, and real-time inference.
•  
• Apply model compression techniques such as quantization, pruning, and distillation for edge and cloud deployments.
•  
• Deploy AI applications using Docker, Kubernetes, and modern model-serving frameworks.
•  
• Implement MLOps/LLMOps practices, CI/CD pipelines, model versioning, monitoring, and observability.

Collaboration & Leadership

• Collaborate with cross-functional teams to integrate AI capabilities into end-to-end products.
•  
• Mentor junior engineers, conduct code reviews, and promote engineering best practices.
•  
• Maintain technical documentation and contribute to architectural decisions.

Preferred Technology Stack

Programming: Python, SQL

AI/ML: PyTorch, TensorFlow, Scikit-learn, Hugging Face, PyTorch Lightning

Generative AI & Agents: LangChain, LangGraph, LlamaIndex, CrewAI, AutoGen, DSPy

LLMs & RAG: OpenAI, Gemini, Anthropic APIs, FAISS, Pinecone, Milvus, Qdrant, Weaviate

Computer Vision & Edge AI: OpenCV, ONNX Runtime, TensorRT, OpenVINO, Tesseract OCR

MLOps/LLMOps: Docker, Kubernetes, MLflow, Kubeflow, Weights & Biases, GitLab CI/CD

Cloud: AWS, Azure, GCP

Monitoring: Prometheus, Grafana, LangSmith, Evidently AI

Databases: PostgreSQL, MongoDB, Redis

Required Skills & Qualifications

• 5+ years of experience in AI/ML, Deep Learning, or related domains.
•  
• Strong proficiency in Python and hands-on experience with PyTorch, TensorFlow, and Hugging Face ecosystem.
•  
• Experience building LLM applications, RAG systems, and Agentic AI solutions.
•  
• Strong understanding of Generative AI, Transformers, Prompt Engineering, and modern NLP techniques.
•  
• Experience in Computer Vision and deploying optimized models in cloud and/or edge environments.
•  
• Hands-on experience with Docker, Kubernetes, CI/CD pipelines, and cloud platforms.
•  
• Proven ability to translate research into scalable production systems.
•  
• Excellent problem-solving, communication, leadership, and mentoring skills.

Education

Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Machine Learning, Data Science, or a related field.

What We Offer

• Opportunity to work on cutting-edge AI and Generative AI solutions.
• Continuous learning, research, and career growth opportunities.
• Collaborative and innovation-driven work culture.
• Opportunity to build impactful, next-generation AI products.

How to Apply

• Please submit your resume, portfolio, and a cover letter outlining your relevant experience and how you can contribute to Aaizel Tech’s success.

Job Description

Our Media Measurement team uses state-of-the-art technologies and rigorous methods to track who is watching what, where, and how they engage with content. Our clients can evaluate who is consuming which content across different media, platforms and devices, and know what the audience thinks about that content. As people consume media content on more channels, and through more devices, than ever before, we are proud to provide a full view on media consumption.

As Data Scientist you will have following main accountabilities: 

• You own together with your team several of our Data Science solutions throughout the full life cycle (brainstorming, design, implementation, productization and maintenance) 
• You develop solutions based on data science, stats and machine learning models 
• You improve methods and tools. Contribute to our communities of practice in the area of Data Science 
• Communicate with non-data scientists in Tech, Operations, Commercial, Product. Understand the domain and the requirements. Explain Data Science principles, concepts, algorithms, and approaches in simple words to different types of audiences 
• Make data your best friends. Understand their strengths and use them. Be aware of their weaknesses and handle those in your solutions 
• Screen the market for potential new Data Science approaches 
• Foster knowledge exchange within the company. Present GfK's Data Science expertise at conferences and workshops 

Qualifications

Now you know what a Data Scientist does. What skills, qualifications & experience do you need for this job? 

• You typically have a Master's degree or PhD that reflects modeling and statistics skills and 6+ years of experience. 
• You enjoy communicating complex methodology and technology to tech and non tech audiences 
• You have expert statistical / machine learning modeling skills (e.g. statistical tests, classification, predictive modelling, handling of missing data, sampling, weighting) 
• You have experience with an analytical programming language (Python) and the respective ecosystem 

Besides the things we really expect you to have, there are some things which would be amazing if you have experience with them: 

• Knowledge of cloud computing environments and tooling (especially AWS) 
• Advanced software development skills (unit testing, CI/CD, Git) 
• Basic skills regarding database handling as SQL 
• Basic knowledge of the always evolving Data Science ecosystem and its frameworks 

Additional Information

• Enjoy a flexible and rewarding work environment with peer-to-peer recognition platforms. 
• Recharge and revitalize with help of wellness plans made for you and your family. 
• Plan your future with financial wellness tools. 
• Stay relevant and upskill yourself with career development opportunities. 

Our Benefits

• Flexible working environment
• Volunteer time off
• LinkedIn Learning
• Employee-Assistance-Program (EAP)

About the Role

We are looking for passionate and driven interns across multiple technology domains including Frontend Development, Backend Development, DevOps, AI/ML, and Data Engineering. This internship offers hands-on experience in real-world projects, collaboration with cross-functional teams, and exposure to modern tools and technologies. 

Domains & Responsibilities 

Frontend Development 

• Build responsive and user-friendly web interfaces  
• Translate UI/UX designs into functional applications  
• Optimize performance and ensure cross-browser compatibility  

 Backend Development 

• Develop APIs and server-side logic  
• Work with databases and data storage solutions  
• Ensure application security and performance  

 DevOps 

• Assist in CI/CD pipeline setup and automation  
• Manage deployments and cloud infrastructure  
• Monitor system performance and reliability  

 AI / Machine Learning 

• Develop and train ML models  
• Work on NLP, automation, or AI-driven features  
• Analyze datasets and evaluate model performance  

 Data Engineering 

• Build and maintain data pipelines (ETL/ELT)  
• Ensure data quality and availability  
• Work with large datasets and optimize data workflows  

 Required Skills (Any Domain) 

• Frontend: HTML, CSS, JavaScript, React/Vue/Angular  
• Backend: Node.js / Python / Java / PHP, APIs, databases  
• DevOps: Linux, Git, CI/CD basics, cloud fundamentals  
• AI/ML: Python, ML basics, TensorFlow/PyTorch/Scikit-learn  
• Data Engineering: SQL, Python, data processing concepts  

 Good to Have 

• Knowledge of Git and version control  
• Basic understanding of cloud platforms (AWS/Azure/GCP)  
• Problem-solving mindset and willingness to learn  
• Exposure to real-world or academic projects  

 Who Should Apply 

• Students or recent graduates in Computer Science, IT, or related fields  
• Candidates with strong interest in any of the above domains  
• Self-learners with project experience are highly encouraged  

 Internship Details 

• Duration: 3–6 months  
• Mode: Remote  
• Certificate + PPO (Pre-Placement Offer) based on performance  

 What You’ll Gain 

• Hands-on experience with real projects  
• Mentorship from experienced professionals  
• Exposure to industry tools and workflows  
• Opportunity to convert to a full-time role 

Contract Job Position - AI Architect / AI Tech Lead

Contract Term - Max 3 -6 Months

Looking For immediate joiners Only

Remote Opportunity

Hands on expereince in AI

Must have experinence in Python

Expereince in LangGraph / Azure AI / Azure Foundry exposure

Must have Ability to provide technical leadership and solution direction

Junior Data Scientist (2–3 Years Experience)

• Strong understanding of Probability & Statistics
• Strong educational background in Statistics or Mathematics (degree/course specialization). 
• Knowledge of core Machine Learning algorithms
• Proficiency in Python
• Experience with Natural Language Processing (NLP)
• Understanding of Transformer-based models
• 2–3 years of hands-on Data Science experience
• Good analytical and problem-solving skills

Senior Data Scientist (ML) – 5+ Years

Required Skills:

• 5+ years of experience in Data Science/ML
• Strong knowledge of Probability & Statistics
• Strong educational background in Statistics or Mathematics (degree/course specialization). 
• Good understanding of core Machine Learning algorithms
• Proficiency in Python, PySpark, and SQL
• Experience with Databricks, Azure ML, SageMaker, or Vertex AI
• Hands-on experience in Natural Language Processing (NLP)
• Understanding of Transformer-based models and architectures
• Ability to build, deploy, and optimize ML solutions at scale

Experience: 6+ years building and operating production ML systems that drive commercial decisions at scale. 

Location: Remote 

To streamline and fast-track screening, please submit your details here (if you haven’t already): https://airtable.com/appbtkr4odapnb5I6/pag05ROZwgz5AaLDG/form 

We’ll review your responses as part of the initial screening process. Please make sure you complete and submit all details through the form to be considered for the next stage. Submissions outside the form may not be considered.

Why This Role Matters

Terrabase builds decisioning infrastructure for enterprise customers: ranked recommendations, scoring pipelines, and policy-governed outputs that drive real commercial action. Our ML systems do not live in notebooks. They run multi-stage evaluation harnesses, apply structured governance rules, backtest against historical outcomes, and ship ranked outputs that customers act on daily.

This role owns the decisioning system end to end. That means the models, the eval harness, the policy layer, the production services, and the technical roadmap for where all of it goes next.

What You Will Do

Own the decisioning and ranking pipeline. Design, extend, and operate the end-to-end system: candidate generation in DuckDB, multi-stage scoring with LightGBM and AutoGluon, post-score policy application, and final ranked output delivery. You understand each layer well enough to debug latency, correctness, and coverage problems quickly, and to design the next version.

Lead the evaluation harness. Our eval pipeline runs multiple gates before any output ships: data health checks, specification validation, business rules enforcement, resolution checks, LLM-as-judge scoring, backtest against historical outcomes, and final output validation. You will own this harness, extend it as the system grows, and ensure every model or pipeline change is measurable and reproducible before it reaches a customer.

Apply policy logic with rigor. Our ML systems operate under structured governance rules that determine which offers apply to which customer segments, under what conditions. You will implement, test, and audit these rules in code, not configure them in a spreadsheet. Every exclusion must be traceable and explainable.

Engineer features that move metrics. Identify and build the behavioral signals, engagement indicators, contract features, and value-band attributes that improve model performance. Close the loop from feature hypothesis through offline evaluation to production monitoring. Own the data contracts between upstream sources and the scoring pipeline.

Build and maintain the production pipeline and service layer. The decisioning system is not a batch notebook. You will write and operate the Python pipeline and service layer that wraps model inference, handles edge cases, versions model artifacts, and connects to downstream consumers. You own CI, test coverage, reproducible training runs, monitoring, and production incidents.

Drive technical direction. Write design documents, lead code review, and set the engineering standard for the decisioning system. Help define the roadmap: what gets built, in what order, and why. Mentor contributors who work alongside you on this system.

Work forward-deployed. You will engage directly with customer stakeholders to understand business context, interpret model outputs, and translate commercial requirements into system constraints. You are accountable for customer delivery, not just model accuracy.

What We Are Looking For

• 6+ years building and operating production ML systems, not prototypes or research work
• Strong Python skills across the full ML lifecycle: data pipelines, feature engineering, model training, inference services, and monitoring
• Production experience with gradient boosting models (LightGBM, XGBoost)
• Hands-on with DuckDB or similar in-process analytical engines for large-scale data processing
• Evaluation discipline: held-out metrics, backtesting against historical data, multi-gate eval pipelines, LLM-as-judge patterns
• Experience applying business rules, policy overrides, or constraint layers on top of model outputs
• Engineering fundamentals: CI pipelines, data contracts, versioned artifacts, test coverage, incident response
• Technical leadership: design docs, code review, roadmap input, mentoring
• Comfort with forward-deployed work: you can run a meeting with a non-technical stakeholder and turn the output into a system requirement
• Comfort inheriting an existing production codebase, improving its structure, and raising reliability without rewriting everything from scratch

Bonus Points

• Experience with next-best-offer engines, customer-level targeting, or recommendation systems at scale
• Experience with AutoML frameworks (AutoGluon or similar) in a production scoring pipeline
• Thompson sampling, multi-armed bandits, or portfolio-level optimization experience
• Exposure to structured data from telecoms, financial services, or retail sectors
• Prior work owning a decisioning or ranking system as the technical lead

Life at Terrabase

We are a sharp, focused, fully remote team that ships to real enterprise customers weekly. You will own a system that drives measurable commercial outcomes, with high autonomy, generous cloud budgets, and a culture that prizes rigor over hype.

Terrabase is an equal-opportunity employer. We celebrate diversity and are committed to building an inclusive environment for every team member.

ey Responsibilities

✅ Architect, develop, and deploy AI-powered enterprise applications and intelligent automation solutions.

✅ Translate business requirements into scalable, secure, and production-ready AI systems.

✅ Build and integrate AI/ML capabilities into enterprise platforms and digital products.

✅ Design cloud-native applications leveraging AWS, Azure, or Google Cloud Platform (GCP).

✅ Develop APIs, microservices, distributed systems, and modern integration frameworks.

✅ Implement DevOps best practices, CI/CD automation, and engineering lifecycle processes.

✅ Utilize AI-assisted development tools to improve productivity and accelerate delivery.

✅ Ensure compliance with security standards, governance frameworks, and data privacy requirements.

✅ Collaborate with cross-functional teams, product stakeholders, and business leaders to deliver innovative solutions.

Required Skills

🔹 5+ years of experience in Software Engineering, Solution Architecture, or Enterprise Application Development.

🔹 Strong programming expertise in *Python, Java, TypeScript, or Go*.

🔹 Hands-on experience integrating AI/ML solutions into enterprise applications.

🔹 Experience with cloud platforms such as *AWS, Azure, or GCP*.

🔹 Strong understanding of *APIs, Microservices, Distributed Systems, and Containerization*.

🔹 Experience with *Agile methodologies, DevOps practices, and CI/CD pipelines*.

🔹 Knowledge of secure software development and enterprise governance standards.

🔹 Excellent problem-solving, communication, and stakeholder management skills.

Good to Have

⭐ Experience with *Machine Learning, Generative AI, Intelligent Automation, or LLM-based solutions*.

⭐ Knowledge of *MLOps, Prompt Engineering, Model Monitoring, AI Validation, and LLM Integration*.

⭐ Experience in *Banking, FinTech, Payments, or other regulated industries*.

⭐ Advanced degree in Computer Science, Artificial Intelligence, Engineering, or related fields.

⭐ Certifications such as *AWS/Azure/GCP Solutions Architect, TOGAF, CKA, or Lean Six Sigma*.

⭐ Experience leading engineering modernization, transformation, or automation initiatives.

⭐ Contributions to open-source projects and a passion for emerging technologies.

Job description:

Interview Venue: H-28, ARV Park, Sector 63, Noida, Uttar Pradesh 201301

Job location: Noida

Experience: 1-2 years

Education: B.Tech or MCA

The procedure for the interview will be as follows:

• 1st Round - Machine Round
• 2nd Round- Communication Round
• 3rd Round – Assignment Round
• 4th Round - HR Round

Job Description:

• Profile: AI/ML Engineer
• Experience: 1-2 yrs
• Qualification : B.Tech/MCA
• Working Days: 5
• Job Nature: Permanent

Roles And Responsibilities:

1) Python Proficiency and API Integration:

Demonstrate strong proficiency in Python programming language.

Design and implement scalable, efficient, and maintainable code for machine learning applications.

Integrate machine learning models with APIs to facilitate seamless communication between different software components.

2) Machine Learning Model Deployment, Training, and Performance:

Develop and deploy machine learning models for real-world applications.

Conduct model training, optimization, and performance evaluation.

Collaborate with cross-functional teams to ensure the successful integration of machine learning solutions into production systems.

3) Large Language Model Understanding and Integration:

Possess a deep understanding of large language models (LLMs) and their applications.

Integrate LLMs into existing systems and workflows to enhance natural language processing capabilities.

Stay abreast of the latest advancements in large language models and contribute insights to the team.

4) Langchain and RAG-Based Systems (e.g., LLamaindex):

Familiarity with Langchain and RAG-based systems, such as LLamaindex, will be a significant advantage.

Work on the design and implementation of systems that leverage Langchain and RAG-based approaches for enhanced performance and functionality.

5) LLM Integration with Vector Databases (e.g., Pinecone):

Experience in integrating large language models with vector databases, such as Pinecone, for efficient storage and retrieval of information.

Optimize the integration of LLMs with vector databases to ensure high-performance and low-latency interactions.

6) Natural Language Processing (NLP):

Expertise in NLP techniques such as tokenization, named entity recognition, sentiment analysis, and language translation.

Experience with NLP libraries and frameworks like NLTK, SpaCy, Hugging Face Transformers

7) Computer Vision:

Proficiency in computer vision tasks such as image classification, object detection, segmentation, and image generation.

Experience with computer vision libraries like OpenCV, PIL, and frameworks like TensorFlow, PyTorch, and Keras.

8) Deep Learning:

Strong understanding of deep learning concepts and architectures, including convolutional neural networks (CNNs) and recurrent neural networks (RNNs).

Proficiency in using deep learning frameworks like TensorFlow, PyTorch, and Keras.

Experience with model optimization, hyperparameter tuning, and transfer learning.

9) Data Manipulation:

Strong skills in data manipulation and analysis using libraries like Pandas, NumPy, and SciPy.

Proficiency in data cleaning, preprocessing, and augmentation techniques.

Perks&Benefits:

• Employees & Family Health Insurance, EPF & ESIC.
• Free late-night meal facility.
• Innumerable in house & outdoor party.
• Various compensations & bonuses.
• No dress Code.
• Festival Celebration.
• Employees' B'day celebration.

Job Description – Data Scientist (Machine Learning & Forecasting)

About the Role

We are looking for a highly skilled Data Scientist with strong expertise in Machine Learning, Traditional Statistical Modelling, Forecasting, and Predictive Analytics. The ideal candidate will have hands-on experience building and deploying end-to-end ML solutions, working with large datasets, and translating business problems into scalable data science solutions.

The role requires a strong foundation in statistics, predictive modelling, feature engineering, model evaluation, and time-series forecasting, along with the ability to collaborate with cross-functional teams to deliver business impact.

Key Responsibilities

• Design, develop, and deploy Machine Learning models for business-critical use cases.
• Build and optimize traditional ML models such as:
• Linear Regression
• Logistic Regression
• Decision Trees
• Random Forest
• Gradient Boosting (XGBoost, LightGBM, CatBoost)
• Support Vector Machines
• Clustering Algorithms
• Develop forecasting solutions using:
• ARIMA / SARIMA
• Prophet
• Exponential Smoothing
• Time-Series Regression Models
• Perform exploratory data analysis (EDA), feature engineering, and data validation.
• Evaluate model performance using appropriate statistical and business metrics.
• Work with structured and semi-structured datasets from multiple sources.
• Collaborate with business stakeholders to understand requirements and translate them into analytical solutions.
• Build scalable data pipelines and support model deployment in production environments.
• Monitor model performance, identify data drift, and implement model retraining strategies.
• Present insights and recommendations to technical and non-technical stakeholders.

Required Skills & Qualifications

• Bachelor's or Master's degree in Computer Science, Statistics, Mathematics, Data Science, Engineering, or a related quantitative field.
• 5+ years of hands-on experience in Data Science, Machine Learning, and Forecasting.

Technical Skills

   Machine Learning

• Strong understanding of supervised and unsupervised learning algorithms.
• Experience with ensemble methods and advanced ML techniques.
• Expertise in model selection, hyperparameter tuning, and performance optimization.

Forecasting & Statistics

• Strong understanding of:
• Time-Series Analysis
• Forecasting Techniques
• Statistical Inference
• Hypothesis Testing
• Probability Distributions
• A/B Testing

Programming

• Advanced proficiency in Python.
• Experience with:
• Pandas
• NumPy
• Scikit-learn
• Statsmodels
• XGBoost / LightGBM
• Prophet

Data & SQL

• Strong SQL skills with experience in complex queries and performance optimization.
• Experience working with large-scale datasets.

Visualization

• Experience with Power BI, Tableau, Matplotlib, Seaborn, or Plotly.
• Cloud & MLOps (Preferred)
• Exposure to AWS, Azure, or GCP.
• Understanding of Docker, Kubernetes, CI/CD, and ML model deployment practices.

Key Competencies

• Strong analytical and problem-solving skills.
• Excellent communication and stakeholder management abilities.
• Ability to work independently in a fast-paced environment.
• Strong business acumen and data-driven decision-making mindset. 

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)

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)

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

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