50+ Machine Learning (ML) Jobs in India

What You’ll Be Doing:

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

What We’re Looking For:

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

JOB DETAILS:

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

- Industry: Global Digital Transformation Solutions Provider

- Experience: 5-10 years

- Job Location: Pune

- CTC Range: Best in Industry

JD for Data Scientist

Hands-on experience with data analysis tools:

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

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

Skilled in machine learning and predictive analytics:

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

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

Expertise in big data technologies:

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

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

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

Must-Haves

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

******

NP - Immediate joiners only

Location-Pune 

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

Key Responsibilities 

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

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

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

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

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

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

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

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

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

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

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

Required Qualifications 

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

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

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

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

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

•Scripting experience using PowerShell and/or Python 

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

•Understanding of cloud security fundamentals and enterprise governance requirements 

Preferred Qualifications 

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

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

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

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

•Experience with observability tools 

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

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

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

Key Responsibilities 

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

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

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

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

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

•Design, train, and optimize virtual assistants enterprise workflows 

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

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

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

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

Required Qualifications 

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

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

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

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

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

•Strong understanding of cloud platforms (Microsoft Azure preferred) 

Preferred Qualifications 

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

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

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

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

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

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

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

Location: Bangalore

Website: https://www.zeuron.ai

Experience: 1 Year

CTC: ₹12 LPA

About the Company

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

About the Role

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

Key Responsibilities

Design, develop, and optimize software/hardware solutions

Work on system architecture, debugging, and performance improvements

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

Participate in code reviews, testing, and deployment processes

Contribute to innovation and continuous improvement initiatives

Requirements

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

1 year of experience (internships/project experience considered)

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

Good understanding of data structures, algorithms, and system design

Problem-solving mindset with strong analytical skills

Preferred Skills

Experience with embedded systems, IoT, or product development

Knowledge of cloud platforms or system-level programming

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

About the Role:

Ctruh is hiring a hands-on Director of Engineering who codes, architects systems, and builds teams. You’ll set the technical foundation, drive engineering excellence, and own the architecture of our AI, 3D, and XR platform.

This is not a pure management role - expect to spend 50–60% of your time writing code, solving deep technical problems, and owning mission-critical systems. As we scale, this role transitions into CTO, taking full ownership of technical vision and long-term strategy.

What You’ll Own:

1. Technical Leadership & Architecture

• Architect Ctruh’s full-stack platform across frontend, backend, infrastructure, and AI.
• Scale core systems: VersaAI engine, rendering pipeline, AR deployment, analytics.
• Make decisions on stack, scalability patterns, architecture, and technical debt.
• Own design for high-performance 3D asset processing, real-time rendering, and ML deployment.
• Lead architectural discussions, design reviews, and set engineering standards.

2. Hands-On Development

• Write production-grade code across frontend, backend, APIs, and cloud infra.
• Build critical features and core system components independently.
• Debug complex systems and optimize performance end-to-end.
• Implement and optimize AI/ML pipelines for 3D generation, CV, and recognition.
• Build scalable backend services for large-scale asset processing and real-time pipelines.
• Develop WebGL/Three.js rendering and AR workflows.

3. Team Building & Engineering Management

• Hire and grow a team of 5–8 engineers initially (scaling to 15–20).
• Establish engineering culture, values, and best practices.
• Build career frameworks, performance systems, and growth plans.
• Conduct 1:1s, mentor engineers, and drive continuous improvement.
• Set up processes for agile execution, deployments, and incident response.

4. Product & Cross-Functional Collaboration

• Work with the founder and product team on roadmap, feasibility, and prioritization.
• Translate product requirements into technical execution plans.
• Collaborate with design for UX quality and technical alignment.
• Support sales and customer success with integrations and technical discussions.
• Contribute technical inputs to product strategy and customer-facing initiatives.

5. Engineering Operations & Infrastructure

• Own CI/CD, testing frameworks, deployments, and automation.
• Create monitoring, logging, and alerting setups for reliability.
• Manage AWS infrastructure with a focus on cost and performance.
• Build internal tools, documentation, and developer workflows.
• Ensure enterprise-grade security, compliance, and reliability.

Tech Stack:

1. Frontend: React.js, Next.js, TypeScript, WebGL, Three.js

2. BackendNode.js, Python, Express/FastAPI, REST, GraphQL

3. AI/ML: PyTorch, TensorFlow, CV models, Stable Diffusion, LLMs, ML pipelines

4. 3D & Graphics: Three.js, WebGL, Babylon.js, glTF, USDZ, rendering optimization

5. Databases: PostgreSQL, MongoDB, Redis, vector databases

6. Cloud & Infra: AWS (EC2, S3, Lambda, SageMaker), Docker, Kubernetes, CI/CD: GitHub Actions, Monitoring: Datadog, Sentry

What We’re Looking For:

1. Must-Haves

• 9+ years of engineering experience, with 3–4 years in technical leadership.
• Deep full-stack experience with strong system design fundamentals.
• Proven success building products from 0→1 in fast-paced environments.
• Hands-on expertise with React/Next.js, Node.js/Python, and AWS.
• AI/ML deployment experience (CV, generative AI, 3D reconstruction).
• Ability to design scalable architectures for high-performance systems.
• Strong people leadership with experience hiring and mentoring teams.
• Ready to code, review, design, and lead from the front.
• Startup mindset: fast execution, problem-solving, ownership.

2. Highly Desirable

• Strong 3D graphics/WebGL/Three.js knowledge.
• Experience with real-time systems, rendering optimizations, or large-scale pipelines.
• Background in B2B SaaS, XR, gaming, or immersive tech.
• Experience scaling engineering teams from 5 → 20+.
• Open-source contributions or technical content creation.
• Experience working closely with founders or executive leadership.

Why Ctruh:

• Hard, meaningful engineering problems at the intersection of AI, 3D, XR, and web tech.
• Build from day zero – architecture, team, and culture.
• Path to CTO as the company scales.
• High autonomy to drive technical decisions.
• Direct founder collaboration on product vision.
• High ownership, high-growth environment.
• Backed by global leaders: Microsoft, Google, NVIDIA, AWS.

Location & Work Culture:

• Location: HSR Layout, Bengaluru
• Schedule: 6 days a week, (5 days-in-office, Saturdays WFH)
• Culture: High-intensity, high-integrity, engineering-first
• Team: Young, ambitious, technically strong

The Ideal Candidate:

You're an engineer at heart and a leader by instinct. You love coding as much as architecting systems. You balance speed with quality, innovate fearlessly, and thrive in ambiguity.

You can:

• Architect microservices in the morning
• Review mission-critical PRs at noon
• Build a Three.js shader in the afternoon
• Run an engineering standup in the evening

You’ve experienced both the pain of poor architecture and the joy of elegant systems - and know how to build things that scale. If you geek out over AI/ML pipelines, 3D rendering, WebGL performance, or building engineering orgs from scratch, you’ll love Ctruh.

Your Responsibilities

what you will wake up to solve.

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

Functional Skills

Scaling Intelligent Workforce through Delivery Excellence

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

Technical Oversight & Execution Charter

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

Tech Superpowers

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

Experience & Relevance

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

Bonus Points (you will thrive if you have)

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

Your Responsibilities

what you will wake up to solve.

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

Functional Skills

1. Scaling Intelligent Workforce through Delivery Excellence

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

2. Technical Oversight & Execution Charter

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

Tech Superpowers

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

Experience & Relevance

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

Bonus Points (you will thrive if you have)

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

Why you’ll love being a ‘Searcian’

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

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

Join the ‘real solvers’

ready to futurify?

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

Title: AI Solutions Architect

Location: Gurgaon

Experience: 2-6 years

Type: Full-Time

About the company:

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

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

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

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

About the role:

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

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

Key responsibilities:

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

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

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

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

·      Lead and mentor a growing AI/Tech team

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

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

Must have skills:

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

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

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

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

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

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

·      Excellent communication and problem-solving skills

Good to have:

·      Open-source contributions or personal GenAI projects

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

·      Experience with MLOps tools

·      Entrepreneurial experience

🔹 Role: Python Engineer – Python & MLOps

📍 Location: Bellandur, Bangalore

🕐 Work Timings: 01:30 PM – 10:30 PM

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

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

🔹 Role Overview

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

🔹 Key Responsibilities

✔ Develop production-grade Python applications using OOP principles

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

✔ Design and optimize REST APIs with OpenAI/Swagger

✔ Implement async programming for high-performance systems

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

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

🔹 Required Skills

✔ Strong Python (OOP, modular design)

✔ MLOps & CI/CD pipeline experience

✔ REST API development

✔ Async programming (async/await, concurrency)

✔ Pandas / Polars & Scikit-learn

✔ JSON Schema–driven development

✔ Testing using PyTest

🔹 Nice to Have

➕ Azure ML SDK

➕ Pydantic

➕ Azure Cosmos DB

➕ Experience with large enterprise platforms

Job Title: Lead Data Architect (AI & Cloud)

Company: Risosu Consulting

About the Role

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

Key Responsibilities

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

Requirements

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

Why Join via Risosu?

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

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

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

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

Key Requirements:

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

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

Job Description – AI Tech Lead

Location: Bangaluru

Experience: 10+ Years

Function: AI Center of Excellence (CoE)

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

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

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

2. Key Responsibilities

A. Solution Architecture & Strategy

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

B. Project Delivery & Execution Leadership

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

C. Technical Hands-on Expertise

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

D. Team Leadership & Mentoring

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

E. Stakeholder & Client Management

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

3. A. Technical Skills

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

B. Functional & Domain Skills

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

C. Leadership & Soft Skills

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

4. Qualifications

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

This role will report to the Chief Technology Officer

You Will Be Responsible For

* Driving decision-making on enterprise architecture and component-level software design to our software platforms' timely build and delivery.

* Leading a team in building a high-performing and scalable SaaS product.

* Conducting code reviews to maintain code quality and follow best practices

* DevOps practice development on promoting automation, including asset creation, enterprise strategy definition, and training teams

* Developing and building microservices leveraging cloud services

* Working on application security aspects

* Driving innovation within the engineering team, translating product roadmaps into clear development priorities, architectures, and timely release plans to drive business growth.

* Creating a culture of innovation that enables the continued growth of individuals and the company

* Working closely with Product and Business teams to build winning solutions

* Led talent management, including hiring, developing, and retaining a world-class team

Ideal Profile

* You possess a Degree in Engineering or a related field and have at least 20+ years of experience as a Software Engineer, with a 10+ years of experience leading teams and at least 4 Years of experience in building a SaaS / Fintech platform.

* Proficiency in MERN / Java / Full Stack.

* Led a team in optimizing the performance and scalability of a product

* You have extensive experience with DevOps environment and CI/CD practices and can train teams.

* You're a hands-on leader, visionary, and problem solver with a passion for excellence.

* You can work in fast-paced environments and communicate asynchronously with geographically distributed teams.

What's on Offer?

* Exciting opportunity to drive the Engineering efforts of a reputed organisation

* Work alongside & learn from best in class talent

* Competitive compensation + ESOPs

About the Company:

E2M Solutions works as a trusted white-label partner for digital agencies. We support agencies with consistent and reliable delivery through services such as website design, web development, eCommerce, SEO, AI SEO, PPC, AI automation, and content writing. Founded on strong business ethics, we are an equal opportunity organization powered by 300+ experienced professionals, partnering with 400+ digital agencies across the US, UK, Canada, Europe, and Australia. At E2M, we value ownership, consistency, and people who are committed to doing meaningful work and growing together. If you’re someone who dreams big and has the gumption to make them come true, E2M has a place for you.

About the Role:

We are seeking a highly skilled Technical Lead – AI who combines deep technical expertise in AI/ML with strong leadership capabilities. The ideal candidate will be responsible for designing AI architectures, leading development teams, and ensuring the successful implementation of AI-driven solutions. This role requires a hands-on technical leader who can guide engineers, solve complex AI problems, and collaborate with cross-functional teams to translate business needs into innovative AI solutions.

Responsibilities:

Technical Leadership:

• Lead the design and development of AI/ML solutions and intelligent automation systems.
• Provide technical guidance and mentorship to AI engineers and developers.
• Conduct architecture reviews, code reviews, and technical evaluations.
• Ensure adoption of best practices in AI model development, testing, and deployment.

AI Solution Development:

• Design and implement machine learning, deep learning, and generative AI models.
• Develop AI-powered solutions such as chatbots, recommendation engines, NLP systems, and predictive analytics models.
• Work on LLM-based applications, prompt engineering, and AI workflow automation.
• Build scalable AI APIs and production-ready AI systems.

Innovation & Research:

• Stay updated with the latest advancements in AI, Machine Learning, and Generative AI technologies.
• Evaluate new tools, frameworks, and technologies to enhance AI capabilities within the organization.
• Contribute to internal AI initiatives and innovation projects.

Required Qualifications:

• 6–8 years of experience in Artificial Intelligence, Machine Learning, or Data Science.
• At least 2 years of experience in a technical leadership or senior engineering role.
• Proven experience building production-level AI applications.

Required Skills:

• Strong programming experience in Python.
• Hands-on experience with Machine Learning frameworks such as, TensorFlow, PyTorch, Scikit-learn
• Experience working with Generative AI and Large Language Models (LLMs), LangChain, Llama Index, or similar AI orchestration frameworks.
• Strong knowledge of Natural Language Processing (NLP).
• Experience building AI APIs and integrating AI into applications.
• Familiarity with vector databases, embeddings, and RAG architectures.
• Hands on knowledge of Full Stack Development.

About the Role

We are looking for a passionate AI/ML Software Engineer to join our product team and help build intelligent, scalable, and production-ready machine learning solutions. You will work closely with product managers, designers, and backend engineers to integrate AI capabilities into core product features and drive data-driven innovation.

Key Responsibilities

• Design, develop, and deploy machine learning models into production environments
• Build and maintain scalable ML pipelines for data processing, training, and inference
• Collaborate with cross-functional teams to identify AI-driven product opportunities
• Translate business requirements into ML solutions and technical implementations
• Optimize model performance, accuracy, and latency for real-time applications
• Integrate AI/ML models with APIs and backend systems
• Monitor model performance and implement continuous improvement strategies
• Ensure best practices in data handling, model versioning, and reproducibility
• Stay updated with the latest advancements in AI/ML and apply them to product innovation

Required Skills & Qualifications

• Bachelor’s engineering degree in Computer Science, AI, Data Science, or related field
• Strong programming skills in Python (experience with Java/Go is a plus)
• Hands-on experience with ML frameworks such as TensorFlow, PyTorch, or Scikit-learn
• Solid understanding of machine learning algorithms and statistical concepts
• Experience in building and deploying ML models in production
• Familiarity with REST APIs, microservices architecture, and cloud platforms (AWS/GCP/Azure)
• Experience with data processing tools (Pandas, NumPy, Spark, etc.)
• Knowledge of version control systems like Git 

Introduction

About Us:

Mercari is a Japan-based C2C marketplace company founded in 2013 with the mission to “Create value in a global marketplace where anyone can buy & sell.” From being the first tech unicorn from Japan before its IPO in 2018 we have come a long way towards becoming a global player and continuously and diligently work towards our transformation journey with a strong focus on our mission.

Since its inception, Mercari Group has worked to grow its services, investing in both our people and technology. Over time Mercari has expanded from being the top player in the C2C marketplace in Japan to new geographies like the U.S. We have also successfully launched new businesses such as Merpay, which is a mobile payment service platform with a vision to create a society where anyone can realize their dreams through a new ecosystem centered not only on payment service but also on credit. Today, Mercari Group is made up of multiple subsidiary businesses including logistics, B2C platform, blockchain, and sports team management.

For our services to be utilized by people worldwide; however, there is still a mountain of work ahead of us. This endeavor naturally requires the capability of the best talent and minds, and that is exactly the reason for us to launch the India Center of Excellence. With your help, we will continue to take on the world stage and strive to grow into a successful global tech company.

Our Culture:

To achieve our mission at Mercari, our organization and each of our employees share the same values and perspectives. Our individual guidelines for action are defined by our four values: Go Bold, All for One, Be a Pro and Move Fast. Our organization is also shaped by our four foundations: Sustainability, Diversity & Inclusion, Trust & Openness, and Well-being for Performance. Regardless of how big Mercari gets, the culture will remain essential to achieving our mission and something we want to preserve throughout our organization. We invite you to read the Mercari Culture Doc which summarizes the behaviors and mindset shared by Mercari and its employees. We continue to build an environment where all of our members of diverse backgrounds are accepted and recognized, and where they can thrive while holding dear to Mercari’s culture.

Work Responsibilities

• Machine learning engineers working in the Recommendation domain develop the functions and services of the marketplace app Mercari through the development and maintenance of machine learning systems like Recommender systems while leveraging necessary infrastructure and companywide platform tools. 
• Mercari is actively applying advanced machine learning technology to provide a more convenient, safer, and more enjoyable marketplace. Machine learning engineers use the cloud and Kubernetes to operate and improve machine learning systems.

Bold Challenges

• We are looking for people who are interested in our services, mission, and values, and want to work where engineers can go bold, use the latest technology, make autonomous decisions, and take on challenges at a rapid pace.
• Develop and optimize machine learning algorithms and models to enhance recommendation system to improve discovery experience of users
• Collaborate with cross-functional teams and product stakeholders to gather requirements, design solutions, and implement features that improve user engagement
• Conduct data analysis and experimentation with large-scale data sets to identify patterns, trends, and insights that drive the refinement of recommendation algorithms
• Utilize machine learning frameworks and libraries to deploy scalable and efficient recommendation solutions.
• Monitor system performance and conduct A/B testing to evaluate the effectiveness of features.
• Continuously research and stay updated on advancements in AI/machine learning techniques and recommend innovative approaches to enhance recommendation capabilities.

Minimum Requirements:

• Over 5-9 years of professional experience in end-to-end development of large-scale ML systems in production
• Strong experience demonstrating development and delivery of end-to-end machine learning solutions starting from experimentation to deploying models, including backend engineering and MLOps, in large scale production systems.
• Experience using common machine learning frameworks (e.g., TensorFlow, PyTorch) and libraries (e.g., scikit-learn, NumPy, pandas)
• Deep understanding of machine learning and software engineering fundamentals
• Basic knowledge and skills related to monitoring system, logging, and common operations in production environment
• Communication skills to carry out projects in collaboration with multiple teams and stakeholders

Preferred skills:

• Experience developing Recommender systems utilizing large-scale data sets
• Basic knowledge of enterprise search systems and related stacks (e.g. ELK)
• Functional development and bug fixing skills necessary to improve system performance and reliability
• Experience with technology such as Docker and Kubernetes
• Experience with cloud platforms (AWS, GCP, Microsoft Azure, etc.)
• Microservice development and operation experience with Docker and Kubernetes
• Utilizing deep learning models/LLMs in production
• Experience in publications at top-tier peer-reviewed conferences or journals

Employment Status

Full-time

Office

Bangalore

Hybrid workstyle

• We believe in high performance and professionalism. We work from office for 2 days/week and work from home 3 days/week
• To build a strong & highly-engaged organization in India, we highly encourage everyone to work from our Bangalore office, especially during the initial office setup phase
• We will continue to review and update the policy to address future organizational needs

Work Hours

• Full flextime (no core time)

*Flexible to choose working hours other than team common meetings

Media

Owned Media

• Mercari Engineering Portal
• AI at Mercari portal
• Mercan - Introduces the people that make Mercari
• Mercari US Blog

Related Articles

• Development Platforms and Platformers: On Rising to the Global Standard Ken Wakasa, Mercari CTO | mercan
• “I'm Not a Talented Engineer” Insists the Member-Turned-Manager Revamping Our Internal CS Tool | mercan
• Personalize to globalize:How Mercari is reshaping their app, their company, and the world | mercan
• The Providers of the Safe and Secure Mercari Experience: The TnS Team, Introduced by Its Members! | mercan

Job Title: Data Analyst (AI/ML Exposure)

Experience: 1–3 Years

Location: Mumbai

Job Description:

We are looking for a Data Analyst with strong experience in data handling, analysis, and visualization, along with exposure to AI/ML concepts. The role involves working with structured and unstructured data (SQL, CSV, JSON), building data pipelines, performing EDA, and deriving actionable insights. Candidates should have hands-on experience with Python (Pandas, NumPy), data visualization tools, and basic knowledge of NLP/LLMs. Exposure to APIs, data-driven applications, and client interaction will be an added advantage.

Skills Required: Python, SQL, Data Analysis, EDA, Visualization, APIs

Apply: Share your resume or connect with us.

Job Title: AI Full Stack Developer

Experience: 4–6 Years

Location: Mumbai / Bengaluru

Job Description:

We are hiring an AI-focused Full Stack Developer with strong experience in Python, React/Next.js, and cloud platforms. The role involves working on LLM integrations (OpenAI/Anthropic), prompt engineering, and building AI-driven workflows such as RAG and agent-based systems. Candidates should have hands-on experience with AWS (Lambda, S3, DynamoDB), API integrations, and end-to-end development. Exposure to async processing (Celery/Redis) and modern frontend frameworks is a plus.

Skills Required: Python, React/Next.js, AWS, APIs, LLMs

Apply: Share your resume or connect with us.

Job Title: AI & Product Engineering Intern

Company: Optimo Capital (Nipun Projects and Finance Pvt. Ltd.) Location: Bengaluru, Karnataka (On-site / Hybrid) Duration: 4–6 months | Immediate / Rolling start Stipend: Based on profile

About Optimo Capital

Optimo Capital is an RBI-registered NBFC and India's first phygital Loan Against Property lender. We serve MSME business owners across 5 states, offering loans of ₹10L–₹2Cr with 4-day disbursal. Our tech team is actively building AI systems that redefine how lending operations work — from smart underwriting to autonomous calling agents to document intelligence and real-time property valuation.

What You'll Work On

You will be embedded in an early-stage fintech team working hands-on to make AI systems actually work in the real world — not in theory, not in demos, but in production. This means getting deep into existing projects — an autonomous AI calling system, an intelligent document extraction pipeline, and agentic AI frameworks — running experiments, figuring out what works and what doesn't, and iterating fast until it does.

Expect a lot of trial and error. Expect to think from first principles. Expect to question assumptions and find creative solutions to problems that don't have a textbook answer. The job is as much about curiosity and persistence as it is about technical skill.

Beyond the engineering, you will also be expected to think like a product person — understanding the business impact of what you build, owning parts of the product, and connecting the dots between what the AI does and why it matters to the business.

What We're Looking For

• Person with fundamental thinking in problem solving Currently pursuing or recently completed a degree in Computer Science, Mathematics, Statistics, or Engineering
• Solid programming fundamentals — Python, NodeJS etc and ability to learn new language if required
• Has shipped something: Internship, a project, a GitHub repo, a hackathon submission, or a research prototype that demonstrates end-to-end thinking
• Understands software systems beyond just writing code — APIs, data flows, system design at a basic level
• Can articulate the product reason behind technical decisions — not just "how" but "why"
• Comfortable working in ambiguity and taking ownership of open-ended problems

What Makes a Great Fit

We're looking for someone who reads about AI systems on weekends not because they have to, but because they're genuinely curious. You should be the kind of person who, when given a problem, immediately starts thinking about the product experience and the architecture simultaneously — and can hold both in your head at once. If you've built an LLM-powered tool, integrated a voice API, parsed messy documents, or simply gone deep on understanding how modern AI systems work under the hood — we'd love to talk.

Job Title: AI Architecture Intern

Company: PGAGI Consultancy Pvt. Ltd.

Location: Remote

Employment Type: Internship

Position Overview

We're at the forefront of creating advanced AI systems, from fully autonomous agents that provide intelligent customer interaction to data analysis tools that offer insightful business solutions. We are seeking enthusiastic interns who are passionate about AI and ready to tackle real-world problems using the latest technologies.

Duration: 6 months

Key Responsibilities:

• AI System Architecture Design: Collaborate with the technical team to design robust, scalable, and high-performance AI system architectures aligned with client requirements.
• Client-Focused Solutions: Analyze and interpret client needs to ensure architectural solutions meet expectations while introducing innovation and efficiency.
• Methodology Development: Assist in the formulation and implementation of best practices, methodologies, and frameworks for sustainable AI system development.
• Technology Stack Selection: Support the evaluation and selection of appropriate tools, technologies, and frameworks tailored to project objectives and future scalability.
• Team Collaboration & Learning: Work alongside experienced AI professionals, contributing to projects while enhancing your knowledge through hands-on involvement.

Requirements:

• Strong understanding of AI concepts, machine learning algorithms, and data structures.
• Familiarity with AI development frameworks (e.g., TensorFlow, PyTorch, Keras).
• Proficiency in programming languages such as Python, Java, or C++.
• Demonstrated interest in system architecture, design thinking, and scalable solutions.
• Up-to-date knowledge of AI trends, tools, and technologies.
• Ability to work independently and collaboratively in a remote team environment

Perks:

- Hands-on experience with real AI projects.

- Mentoring from industry experts.

- A collaborative, innovative and flexible work environment

Compensation:

- Joining Bonus: A one-time bonus of INR 2,500 will be awarded upon joining.

- Stipend: Base is INR 8000/- & can increase up to 20000/- depending upon performance matrix.

After completion of the internship period, there is a chance to get a full-time opportunity as an AI/ML engineer (Up to 12 LPA).

Preferred Experience:

• Prior experience in roles such as AI Solution Architect, ML Architect, Data Science Architect, or AI/ML intern.
• Exposure to AI-driven startups or fast-paced technology environments.
• Proven ability to operate in dynamic roles requiring agility, adaptability, and initiative.

Job Title : Azure Data Scientist (AI/ML)

Experience : 5 to 10 Years

Location : Bengaluru

Work Mode : Hybrid (4 Days WFO, Tue to Fri – Non-Negotiable)

Notice Period : Immediate Joiner

💡 Role Overview :

We are looking for a highly skilled Azure Data Scientist with strong expertise in AI/ML, Python, and cloud-based data platforms. The role involves building scalable ML solutions, working on GenAI & RAG use cases, and delivering business impact through data-driven insights.

🔥 Mandatory Skills :

Python, Azure Machine Learning, Databricks, AI/ML model development (5+ yrs), Statistics & Probability, EDA & Data Modeling, Machine Learning algorithms, GenAI/RAG experience

✅ Key Responsibilities :

• Design, develop, and deploy AI/ML models to solve complex business problems
• Perform Exploratory Data Analysis (EDA) for data cleaning, discovery, and insights
• Build and optimize ML pipelines using Azure Machine Learning & Databricks
• Work on GenAI applications, RAG implementations, and advanced analytics solutions
• Collaborate with data engineers, business stakeholders, and domain experts
• Translate complex data into actionable business insights
• Manage model lifecycle (development, validation, deployment, monitoring)
• Communicate model outputs and insights to technical & non-technical stakeholders
• Drive innovation and contribute to AI/ML best practices and strategy

🧠 Required Skills (Must Have) :

• Strong experience in Python (ML/AI development)
• Hands-on with Azure Machine Learning & Databricks
• Deep understanding of Mathematics, Probability, and Statistics
• Expertise in Machine Learning & Data Science methodologies
• Experience in EDA, data visualization, and model development
• Exposure to GenAI, RAG, and ML application development
• Minimum 5+ years of experience in AI/ML model development
• Strong problem-solving and analytical skills

➕ Good to Have :

• Experience with MLOps practices
• Domain knowledge in Energy / Oil & Gas value chain
• Experience in data visualization tools
• Team collaboration or mentoring experience

🤝 What We’re Looking For :

• Strong communication & stakeholder management skills
• Ability to work in a cross-functional, global team environment
• Self-driven, adaptable, and innovation-focused mindset

📝 Interview Process :

1. Geektrust Assessment (Assemble)
2. Technical Interview
3. Fitment Round
4. Client Round

Python Developer (Performance Optimization Focus)

Experience: 3–5 Years

Location: Remote (India-based candidates only)

Employment Type: Full-time

Role Overview

We are seeking a Python Developer with a strong focus on performance optimization and system efficiency. In this role, you will identify bottlenecks, enhance system performance, and contribute to building scalable, high-performance applications in a Linux-based environment.

Key Responsibilities

• Analyze and troubleshoot performance bottlenecks in applications and systems
• Optimize code, database queries, and architecture for scalability and speed
• Design, develop, test, and maintain robust Python applications
• Work with large datasets and improve data processing efficiency
• Collaborate with cross-functional teams to improve system reliability and performance
• Monitor system performance and implement proactive improvements
• Write clean, maintainable, and efficient code following best practices

Required Skills & Qualifications

• 3–5 years of hands-on experience in Python development
• Strong expertise in performance tuning and optimization techniques
• Experience with debugging and profiling tools
• Solid understanding of data structures and algorithms
• Experience with REST APIs and backend development
• Strong analytical and problem-solving skills

Linux & System Knowledge (Must-Have)

• Comfortable working in Linux/Unix environments
• Command-line proficiency, including:
• File editing (vi, nano)
• File permissions (chmod, chown)
• File downloads (wget, curl)
• Basic file and directory operations

Basic Python Knowledge (Interview Scope)

• Writing simple scripts and reusable functions
• String manipulation and data handling
• Example task: Count words in a file/string efficiently

Good to Have

• Familiarity with AI/ML concepts or tools
• Experience optimizing data-intensive or distributed systems
• Exposure to cloud platforms (AWS, GCP, Azure)

Why Join Us

• Work on performance-critical systems with real-world impact
• Fully remote work environment
• Opportunity to work with modern, scalable technologies
• Collaborative, growth-focused team culture

Key Responsibilities:

• Develop and deploy machine learning, deep learning, and NLP models for various business use cases.
• Build end-to-end ML pipelines including data preprocessing, feature engineering, training, evaluation, and production deployment.
• Optimize model performance and ensure scalability in production environments.
• Work closely with data scientists, product teams, and engineers to translate business requirements into AI solutions.
• Conduct data analysis to identify trends and insights.
• Implement MLOps practices for versioning, monitoring, and automating ML workflows.
• Research and evaluate new AI/ML techniques, tools, and frameworks.
• Document system architecture, model design, and development processes.

Required Skills:

• Strong programming skills in Python (NumPy, Pandas, Scikit-learn, TensorFlow, PyTorch, Keras).
• Hands-on experience in building and deploying, finetuning ML/DL models in production.
• Good understanding of machine learning algorithms, neural networks, NLP, and computer vision.
• Experience with REST APIs, Docker, Kubernetes, and cloud platforms (AWS/GCP/Azure).
• Working knowledge of MLOps tools such as MLflow, Airflow, DVC, or Kubeflow.
• Familiarity with data pipelines and big data technologies (Spark, Hadoop) is a plus.
• Strong analytical skills and ability to work with large datasets.
• Excellent communication and problem-solving abilities.
• Experience in deploying models using cloud services (AWS Sagemaker, GCP Vertex AI, etc.).
• Experience in LLM fine-tuning or Generative AI, Voice AI, is an added advantage.

Educational Qualification:

• Bachelor’s or Master’s degree in Computer Science, Data Science, AI, Machine Learning, IT, from IIT/NIT colleges strongly preferred

Key Requirements / Skills

• 6+ years of overall experience in software development with strong expertise in building scalable web applications.
• 2+ years of experience as a Technical Lead, managing development teams and driving project delivery.
• Strong technical decision-making ability, including architecture design, technology selection, and implementation of best practices.
• Front-end expertise: Strong experience in React, JavaScript, TypeScript, and building responsive and user-friendly UI/UX.
• Back-end development: Hands-on experience with Node.js, RESTful APIs, API design, and server-side architecture.
• AI/ML knowledge: Experience in implementing AI/ML models or integrating AI-based solutions to solve business problems.
• Cloud & DevOps exposure: Experience with AWS/Azure, understanding of CI/CD pipelines, and cloud-based deployments.
• Code quality & best practices: Experience in code reviews, Git version control, and ensuring maintainable and secure code.
• Team leadership: Ability to mentor developers, guide technical discussions, and collaborate across teams.
• Strong communication skills to effectively interact with technical and non-technical stakeholders.
• Experience working in high-compliance environments such as healthcare systems is a plus.

Education Qualifications:

• B.Tech/M.Tech in CSE/IT/AI/ML from a good university

EasySLR is pioneering the future of systematic literature reviews through AI and innovative technologies. Our platform, recognized by industry leaders and academic communities alike, redefines the way researchers conduct reviews, making the process faster, smarter, and more intuitive. We've been at the forefront of AI-driven research, presenting at major conferences and setting new standards in evidence synthesis. If you are a visionary leader with a passion for technology and a drive to make a significant impact, we want you to join our mission to transform the research landscape.

Responsibilities :

- Lead and mentor a team of talented engineers, fostering a culture of innovation, collaboration, and continuous learning.

- Architect and oversee the development of a scalable, high-performance platform that integrates cutting-edge AI technologies and industry best practices.

- Drive the engineering strategy, ensuring alignment with our product vision and business goals.

- Collaborate closely with cross-functional teams, including product, design, and AI experts, to deliver a world-class product experience.

- Ensure the robustness, security, and scalability of our infrastructure, leveraging your deep expertise in cloud computing and full-stack development.

- Stay ahead of emerging technologies, incorporating the latest advancements into our platform and maintaining our competitive edge.

- Cultivate a high-performing engineering team through effective hiring, coaching, and professional development opportunities.

Requirements :

- 4+ years of experience in software engineering, with a proven track record of leading high-performing engineering teams.

- Expertise in full-stack development, with hands-on experience in Python, Node.js, and frameworks like Next.js.

- Extensive experience with cloud platforms, particularly AWS, and familiarity with tools like AWS Lambda, AWS CDK, and containerization technologies.

- Strong background in designing and scaling complex, distributed systems with a focus on performance and security.

- Experience in AI/ML-driven product development is a significant plus.

- Exceptional problem-solving skills, with a strategic mindset and the ability to make data-driven decisions.

- Excellent communication skills, with the ability to articulate complex technical concepts to non-technical stakeholders.

What We Offer :

- The opportunity to lead a cutting-edge platform at the intersection of AI and systematic literature reviews.

- Competitive compensation and a clear path to executive leadership.

- A vibrant, inclusive work culture that values diversity, innovation, and work-life balance.

- The chance to make a meaningful impact in a fast-growing, AI-first SaaS company shaping the future of research.

Ready to lead the engineering efforts that will drive the next generation of AI-driven systematic reviews? Join us at EasySLR and be part of a team that's revolutionizing the research process. Apply now and embark on an exciting journey at the forefront of technology and innovation

Generative AI System Design

• Architect and implement end-to-end LLM-powered applications
• Build scalable RAG pipelines (chunking, embeddings, hybrid search, reranking)
• Design and implement agent-based workflows (tool calling, multi-step reasoning, orchestration)
• Integrate LLM APIs such as OpenAI and Anthropic, along with open-source models
• Implement structured output validation, grounding strategies, and hallucination mitigation
• Optimize inference cost, latency, and token efficiency
• Design evaluation pipelines for performance, accuracy, and safety

2️⃣ Backend & Microservices Engineering

• Design scalable backend systems using Python
• Build REST and async APIs using FastAPI / Django
• Architect and implement microservices with clear service boundaries
• Implement service-to-service communication (REST, gRPC, event-driven messaging)
• Work with message brokers (Kafka / RabbitMQ)
• Optimize database performance (PostgreSQL, MongoDB)
• Implement caching strategies (Redis)
• Build observability: logging, monitoring, distributed tracing

3️⃣ Cloud-Native Architecture & DevOps

• Design and deploy containerized services using Docker
• Orchestrate services using Kubernetes
• Implement CI/CD pipelines
• Ensure system scalability, resilience, and fault tolerance
• Apply distributed systems principles:
• Circuit breakers
• API gateway patterns
• Load balancing
• Horizontal scaling
• Saga patterns
• Zero-downtime deployments

About the Role

We are looking for a highly skilled Data Scientist with strong expertise in Machine Learning, MLOps, and Generative AI. The ideal candidate will have hands-on experience in building scalable ML models, deploying them in production, and working with modern AI frameworks, including GenAI technologies.

Key Responsibilities

·      Design, develop, and deploy machine learning models for real-world business problems

·      Work on end-to-end ML lifecycle: data preprocessing, model building, evaluation, deployment, and monitoring

·      Implement and manage MLOps pipelines for scalable and reproducible workflows

·      Utilize tools like MLflow for experiment tracking, model versioning, and lifecycle management

·      Develop and integrate Generative AI (GenAI) solutions such as LLM-based applications

·      Collaborate with cross-functional teams (engineering, product, business) to translate requirements into AI solutions

·      Optimize model performance and ensure production stability

·      Stay updated with the latest advancements in AI/ML and GenAI ecosystems

Required Skills & Qualifications

·      4+ years of experience in Data Science / Machine Learning

·      Strong programming skills in Python

·      Hands-on experience with ML modeling techniques (supervised, unsupervised, NLP, etc.)

·      Solid understanding of MLOps practices and tools

·      Experience with MLflow or similar model lifecycle tools 

·      Practical experience in Generative AI (GenAI), including working with LLMs

·      Experience with libraries/frameworks like Scikit-learn, TensorFlow, PyTorch

·      Strong understanding of data structures, algorithms, and statistics

·      Experience with cloud platforms (AWS/GCP/Azure) is a plus

Good to Have

·      Experience with LLM fine-tuning, prompt engineering, or RAG pipelines

·      Exposure to Docker, Kubernetes, and CI/CD pipelines

·      Knowledge of data engineering workflows 

• 10+ years of software development experience
• 3+ years in a technical leadership role
• Strong expertise in Python and SQL
• Experience building scalable APIs and backend systems
• Solid understanding of database design and performance tuning
• Experience with Azure cloud services (AWS familiarity preferred)
• Working knowledge of ML/AI integration in enterprise systems
• Experience in client-facing or consulting environments preferred
• Experience with Databricks or modern data platforms
• Exposure to ETL tools such as Talend
• Experience with BI tools (e.g., Power BI)
• Exposure to regulated domains such as Pharma, Healthcare

Job Title: Senior AI/ML Engineer/Team Lead

Location: Gurugram, Haryana

Employment Type: Full-Time

Experience: 4-9 Years

CTC: Up to 15LPA

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 Senior 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:
• 4+ 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.

Join Aaizel Tech as a Senior AI/ML Engineer and lead the development of innovative, scalable AI solutions that transform industries and drive digital excellence!

🚀 Hiring: AI/M and Gen AI Engineer

⭐ Experience: 5+ Years

⭐ Work Mode:- Remote

⏱️ Notice Period: Immediate Joiners

(Only immediate joiners & candidates serving notice period)

🌟 About the Role

We are looking for a highly skilled AI/ML Software Engineer to design, build, and productionize enterprise-grade AI solutions. This role focuses on Generative AI, RAG systems, and AI agent–driven automation, with deployment on Microsoft Azure.

You will collaborate with cross-functional teams including architects, engineers, and business stakeholders to deliver scalable and secure AI solutions that create real business impact.

🔑 Mandatory Skills (Must Have)

• ✅ Azure AI Ecosystem (Azure Machine Learning, Azure OpenAI, Cognitive Services)
• ✅ Generative AI & RAG Systems (vector embeddings, retrieval pipelines)
• ✅ Strong Software Engineering + MLOps (CI/CD, containerization, scalable deployments)

💼 Key Responsibilities

• Design, develop, and deploy AI/ML models in production environments
• Build and optimize RAG-based applications and AI agent workflows
• Develop scalable data pipelines and integrate with enterprise systems
• Implement MLOps practices for continuous deployment and monitoring
• Work with big data tools to process large-scale datasets
• Ensure security, scalability, and performance of AI systems
• Collaborate with stakeholders to translate business problems into AI solutions

🧠 Required Experience & Skills

• 5–8 years of hands-on experience in AI/ML development
• Strong programming and software engineering expertise
• Experience with Azure services (ML, Data Lake, OpenAI, Cognitive Services)
• Knowledge of vector databases and embedding models
• Experience with Databricks, Azure Data Factory, or Kafka
• Familiarity with multi-agent systems / agentic AI frameworks
• Proficiency in TensorFlow, PyTorch, Keras, or Scikit-learn
• Background in NLP, Computer Vision, or Deep Learning
• Experience with SQL/NoSQL databases and ETL pipelines
• Strong analytical and problem-solving skills 

We are looking for a skilled ML Engineer with 3–5 years of experience in building and deploying production-grade AI solutions, particularly around LLMs, RAG systems, and agentic AI frameworks. The role involves designing end-to-end ML architectures, optimizing models at scale, and delivering client-ready AI solutions. You will collaborate closely with stakeholders, mentor junior engineers, and drive AI projects from experimentation to production.

What will you need to be successful in this role?

Core Technical Skills

• Strong hands-on experience with Python for ML/AI (NumPy, Pandas, Scikit-learn, PyTorch/TensorFlow)

• Proven experience deploying production LLM applications with 1M+ tokens processed

• Advanced prompt engineering expertise including ReAct, meta-prompting, and function calling

• Production experience with RAG systems including hybrid search and re-ranking

• Deep understanding of embedding models and vector databases at scale

• Experience with agentic AI frameworks (LangGraph, CrewAI, or AutoGen)

• Strong knowledge of LLM evaluation frameworks (RAGAS, LLM-as-judge patterns)

• Experience implementing multi-agent systems and orchestration

• Proficiency with cloud ML platforms (AWS SageMaker, Azure ML, or Vertex AI)

Advanced Capabilities

• Experience with model fine-tuning (LoRA, QLoRA, PEFT, instruction tuning)

• Knowledge of knowledge graphs and graph-based RAG implementations

• Understanding of model hosting, inference optimization, and cost management

• Experience with MLOps pipelines, CI/CD for ML, and model versioning

• Ability to architect end-to-end ML solutions from data ingestion to deployment

• Experience with data pipelines and ETL for ML workflows

• Proficiency in containerization and orchestration (Docker, Kubernetes)

Client Engagement & Delivery

• Experience presenting technical solutions to clients and stakeholders

• Ability to translate business requirements into technical ML solutions

• Track record of delivering client POCs and production implementations

• Experience creating technical documentation and implementation guides

Good to have

• Experience hosting private LLMs (7B-13B models on-premises or cloud)

• Knowledge of graph databases (Neo4j) and graph neural networks

• Experience with streaming and real-time ML inference

• Published research papers or contributions to open-source ML projects

• DeepLearning.AI certifications in Agentic AI, RAG, or Finetuning

• AWS/Azure ML certifications or working towards them

Competencies

• Excellent verbal and written communication skills

• Strong mentoring ability for junior ML engineers

• Self-driven with ability to work independently on complex problems

• Excellent problem-solving skills with systematic debugging approach

• Proactive ownership of projects from ideation to deployment

• Ability to stay current with rapidly evolving AI/ML landscape

• Excellent academic record – B.E./B.Tech, MCA,

Who are we aka "About Us":

We are an early-stage Fintech Startup - working on exciting Fintech Products for some of the Top 5 Global Banks and building our own. If you are looking for a place where you can make a mark and not just be a cog in the wheel, Baker street Fintech Pvt Ltd (Parent Company) might be the place for you. We have a flat, ownership-oriented culture, and deliver world-class quality. You will be working with a founding team that has delivered over 26 industry-leading product experiences and won the Webby awards for Digital Strategy. In short, a bleeding edge team. 

As Cambridge Wealth, we are well-established in the wealth and mutual fund distribution segment, having won awards from BSE Star as well as Mutual Fund houses. Our UHNI/HNI/NRI clients include renowned professionals from various industries. 

What are we looking for a.k.a “The JD” :

We are seeking a skilled and detail-oriented Data Analyst to join our product team. As a Data Analyst, you will play a crucial role in extracting, analysing, and interpreting complex financial data to drive strategic decision-making and optimize our data solutions. The ideal candidate should possess a strong foundation in SQL / NoSQL databases, Python programming, and proficiency in tools like PostgreSQL and Excel. A deep understanding of financial concepts is also a plus. Additionally, having an interest in business intelligence tools and machine learning will be valuable for this role.

Responsibilities:

• Proficient in writing complex SQL Queries
• Utilize Python for data manipulation, analysis, and visualisation, using libraries such as pandas, matplotlib, psycopg etc.
• Perform database optimization, indexing, and query tuning to ensure high performance.
• Monitor and maintain data quality, troubleshoot data-related issues, and implement solutions to optimize data integrity and performance.
• Design, configure, and maintain PostgreSQL databases
• Set up and manage database clusters, replication, and backups for disaster recovery

Preferred Qualifications:

• Intermediate-level Excel skills for data analysis and reporting.
• Strong communication skills to present findings effectively and recommendations to both technical and non-technical stakeholders.
• Detail-oriented mindset with a commitment to data accuracy and quality.

*(Only Applicants who have finished their educational commitments are requested to apply)

Not sure whether you should apply? Here's a quick checklist to make things easier. You are someone who:

• Has worked (1-3 years preferably) or is looking to work specifically with an early-stage startup.
• You are ready to be a part of a Zero To One Journey which implies that you shall be involved in building fintech products and process from the ground up.
• You are comfortable to work in an unstructured environment with a small team where you decide what your day looks like and take initiative to take up the right piece of work, own it and work with the founding team on it.
• This is not an environment where someone will be checking up on you every few hours. It is up to you to schedule check-ins whenever you find the need to, else we assume you are progressing well with your tasks. You will be expected to find solutions to problems and suggest improvements.
• You want complete ownership for your role & be able to drive it the way you think is right.
• You can be a self-starter and take ownership of deliverables to develop a consensus with the team on approach and methods and deliver to them.
• Are looking to stick around for the long term and grow with the company.

🤖 Data Scientist – Frontier AI for Data Platforms & Distributed Systems (4–8 Years)

Experience: 4–8 Years

Location: Bengaluru (On-site / Hybrid)

Company: Publicly Listed, Global Product Platform

🧠 About the Mission

We are building a Top 1% AI-Native Engineering & Data Organization — from first principles.

This is not incremental improvement.

This is a full-stack transformation of a large-scale enterprise into an AI-native data platform company.

We are re-architecting:

• Legacy systems → AI-native architectures
• Static pipelines → autonomous, self-healing systems
• Data platforms → intelligent, learning systems
• Software workflows → agentic execution layers

This is the kind of shift you would expect from companies like Google or Microsoft —

Except here, you will build it from day zero and scale it globally.

🧠 The Opportunity: This role sits at the intersection of three high-impact domains:

1. Frontier AI Systems: Large Language Models (LLMs), Small Language Models (SLMs), and Agentic AI

2. Data Platforms: Warehouses, Lakehouses, Streaming Systems, Query Engines

3. Distributed Systems: High-throughput, low-latency, multi-region infrastructure

We are building systems where:

• Data platforms optimize themselves using ML/LLMs
• Pipelines are autonomous, self-healing, and adaptive
• Queries are generated, optimized, and executed intelligently
• Infrastructure learns from usage and evolves continuously

This is: AI as the control plane for data infrastructure

🧩 What You’ll Work On

You will design and build AI-native systems deeply embedded inside data infrastructure.

1. AI-Native Data Platforms

• Build LLM-powered interfaces:
• Natural language → SQL / pipelines / transformations
• Design semantic data layers:
• Embeddings, vector search, knowledge graphs
• Develop AI copilots:
• For data engineers, analysts, and platform users

2. Autonomous Data Pipelines

• Build self-healing ETL/ELT systems using AI agents
• Create pipelines that:
• Detect anomalies in real time
• Automatically debug failures
• Dynamically optimize transformations

3. Intelligent Query & Compute Optimization

• Apply ML/LLMs to:
• Query planning and execution
• Cost-based optimization using learned models
• Workload prediction and scheduling
• Build systems that:
• Learn from query patterns
• Continuously improve performance and cost efficiency

4. Distributed Data + AI Infrastructure

• Architect systems operating at:
• Billions of events per day
• Petabyte-scale data
• Work with:
• Distributed compute engines (Spark / Flink / Ray class systems)
• Streaming systems (Kafka-class infra)
• Vector databases and hybrid retrieval systems

5. Learning Systems & Feedback Loops

• Build closed-loop AI systems:
• Execution → feedback → model updates
• Develop:
• Continual learning pipelines
• Online learning systems for infra optimization
• Experimentation frameworks (A/B, bandits, eval pipelines)

6. LLM & Agentic Systems (Infra-Aware)

• Build agents that understand data systems
• Enable:
• Autonomous pipeline debugging
• Root cause analysis for infra failures
• Intelligent orchestration of data workflows

🧠 What We’re Looking For

Core Foundations

• Strong grounding in:
• Machine Learning, Deep Learning, NLP
• Statistics, optimization, probabilistic systems
• Distributed systems fundamentals
• Deep understanding of:
• Transformer architectures
• Modern LLM ecosystems

Hands-On Expertise

• Experience building:
• LLM / GenAI systems (RAG, fine-tuning, embeddings)
• Data platforms (warehouse, lake, lakehouse architectures)
• Distributed pipelines and compute systems
• Strong programming skills:
• Python (ML/AI stack)
• SQL (deep understanding — query planning, optimization mindset)

Systems Thinking (Critical)

You think in systems, not components.

• Built or worked on:
• Large-scale data pipelines
• High-throughput distributed systems
• Low-latency, high-concurrency architectures
• Understand:
• Query optimization and execution
• Data partitioning, indexing, caching
• Trade-offs in distributed systems

🔥 What Sets You Apart (Top 1%)

• Built AI-powered data platforms or infra systems in production
• Designed or contributed to:
• Query engines / optimizers
• Data observability / lineage systems
• AI-driven infra or AIOps platforms
• Experience with:
• Multi-modal AI (logs, metrics, traces, text)
• Agentic AI systems
• Autonomous infrastructure
• Worked on systems at scale comparable to:
• Google (BigQuery-like systems)
• Meta (real-time analytics infra)
• Snowflake / Databricks (lakehouse architectures)

🧬 Ideal Background (Not Mandatory)

We often see strong candidates from:

• Data infrastructure or platform engineering teams
• AI-first startups or research-driven environments
• High-scale product companies

Experience building:

• Internal platforms used by 1000s of engineers
• Systems serving millions of users / high throughput workloads
• Multi-region, distributed cloud systems

🧠 The Kind of Problems You’ll Solve

• Can LLMs replace traditional query optimizers?
• How do we build self-healing data pipelines at scale?
• Can data systems learn from every query and improve automatically?
• How do we embed reasoning and planning into infrastructure layers?
• What does a fully autonomous data platform look like?

Background: We Commonly See (But Not Limited To)

Our team often includes engineers from top-tier institutions and strong research or product backgrounds, including:

• Leading engineering schools in India and globally
• Engineers with experience in top product companies, AI startups, or research-driven environments
• That said, we care far more about demonstrated ability, depth, and impact than pedigree alone.

🧭 Tech Lead (Backend / Fullstack | 7–10 Years)

Location: Bangalore (On-Site, Hybrid)

Company Type: Public-Listed Product Company

We’re Building a “Top 1% Engineering Org”

We’re building a high-talent-density, AI-first R&D organization from scratch — inside a publicly listed company undergoing a full-scale transformation.

Think:

→ Rewriting legacy systems into AI-native architectures

→ Embedding LLMs + Agentic AI into core workflows

→ Reimagining platforms, infra, and data systems for the next decade

This is the kind of shift you’d expect from Google, Microsoft, or Meta —

Except you get to build it from day 0 → scale it globally.

About the Role / Team

We are building a next-generation AI-first R&D organization in Bengaluru, focused on solving complex problems across LLMs, Agentic AI systems, distributed computing, and enterprise-scale architectures.

This initiative is part of a publicly listed global company investing heavily in AI-driven transformation, re-architecting its platforms into intelligent, autonomous systems powered by large language models, workflows, and decision engines.

You will be working on:

• Agentic AI systems & LLM-powered workflows
• Distributed, scalable backend systems
• Enterprise-grade AI platforms
• Automation-first engineering environments

🚀 The Mandate

Lead execution of mission-critical systems while staying hands-on — bridging architecture and delivery.

🧩 What You’ll Do

• Own end-to-end delivery of complex engineering initiatives (0→1, 1→N)
• Design systems across backend + frontend (if fullstack)
• Translate ambiguous problems into structured technical solutions
• Drive engineering best practices, code quality, and velocity
• Mentor engineers and elevate team performance
• Collaborate with stakeholders on roadmap and execution strategy

🧠 What We’re Looking For

• Strong experience in backend systems + optional frontend frameworks
• Proven ability to lead projects and deliver at scale
• Solid understanding of system design and architecture patterns
• Ability to balance speed vs quality vs scalability trade-offs
• Strong communication and leadership without authority
• Strong coding skills in Python / Java / Go / Node.js
• Solid understanding of data structures, system design basics, and backend architecture
• Experience building scalable APIs and services
• Familiarity or curiosity around AI/LLMs, async systems, or event-driven design
• Strong debugging, problem-solving, and ownership mindset

Nice to Have

• Experience integrating LLMs, vector databases, or AI pipelines
• Contributions to architecture at scale
• Experience with Agentic AI / LLM orchestration frameworks
• Background in product engineering or platform companies
• Exposure to global-scale systems (millions of users / high throughput)

🔥 What Sets You Apart

• Experience leading platform builds or major system rewrites
• Exposure to AI systems, LLM integrations, or intelligent workflows
• Built platforms used by millions of users / high-throughput systems
• Experience with event-driven systems, stream processing, or infra platforms
• Prior work on AI/ML platforms, model serving, or intelligent systems

Background: We Commonly See (But Not Limited To)

• Our team often includes engineers from top-tier institutions and strong research or product company or DeepTech or AI Product backgrounds, including:
• Leading engineering schools in India and globally
• Engineers with experience in top product companies, AI startups, or research-driven environments
• That said, we care far more about demonstrated ability, depth, and impact than pedigree alone.

🚨 We’re Building a “Top 1% Engineering Org”

We’re building a high-talent-density, AI-first R&D organization from scratch — inside a publicly listed company undergoing a full-scale transformation.

Think:

→ Rewriting legacy systems into AI-native architectures

→ Embedding LLMs + Agentic AI into core workflows

→ Reimagining platforms, infra, and data systems for the next decade

This is the kind of shift you’d expect from Google, Microsoft, or Meta —

Except you get to build it from day 0 → scale it globally.

About the Role / Team

We are building a next-generation AI-first R&D organization in Bengaluru, focused on solving complex problems across LLMs, Agentic AI systems, distributed computing, and enterprise-scale architectures.

This initiative is part of a publicly listed global company investing heavily in AI-driven transformation, re-architecting its platforms into intelligent, autonomous systems powered by large language models, workflows, and decision engines.

You will be working on:

• Agentic AI systems & LLM-powered workflows
• Distributed, scalable backend systems
• Enterprise-grade AI platforms
• Automation-first engineering environments

🚀 The Mandate

Own and evolve the technical backbone of an AI-first enterprise platform.

You will define architecture across LLM-powered systems, distributed services, and data platforms — and lead critical transformations from legacy → AI-native systems.

🧩 What You’ll Do

• Architect large-scale distributed systems powering AI-driven workflows
• Lead 0→1 and 1→N platform builds (LLM integrations, agentic systems, orchestration layers)
• Redesign legacy systems into scalable, modular, AI-native architectures
• Drive system design excellence across teams (APIs, infra, observability, reliability)
• Make high-stakes decisions on trade-offs (latency, cost, scalability, model performance)
• Mentor senior engineers and influence engineering culture/org standards
• Partner with product, data, and leadership on long-term technical strategy

🧠 What We’re Looking For

• Proven track record building high-scale backend or platform systems
• Deep expertise in distributed systems, microservices, cloud (AWS/GCP/Azure)
• Strong exposure to data systems/infra / Data / real-time architectures
• Experience or strong interest in LLMs, GenAI, or AI system design
• Exceptional system design, abstraction, and problem-solving ability
• High ownership mindset — you think in terms of systems, not tickets
• Strong coding skills in Python / Java / Go / Node.js
• Solid understanding of data structures, system design basics, and backend architecture
• Experience building scalable APIs and services
• Familiarity or curiosity around AI/LLMs, async systems, or event-driven design
• Strong debugging, problem-solving, and ownership mindset
• Solve hard system problems (latency, scale, reliability)
• Drive cross-team technical decisions and standards
• Mentor senior engineers and influence org-wide architecture 
• Design large-scale distributed systems and backend platforms
• Mentorship & Technical Leadership 
• Expertise in system design, scalability, and performance optimization

Nice to Have

• Experience integrating LLMs, vector databases, or AI pipelines
• Contributions to architecture at scale
• Experience with Agentic AI / LLM orchestration frameworks
• Background in product engineering or platform companies
• Exposure to global-scale systems (millions of users / high throughput)

🔥 What Sets You Apart

• Built platforms used by millions of users / high-throughput systems
• Experience with event-driven systems, stream processing, or infra platforms
• Prior work on AI/ML platforms, model serving, or intelligent systems

Role: ML Engineer

Location: Remote

Experience: 5+ Years

𝗞𝗲𝘆 𝗦𝗸𝗶𝗹𝗹𝘀 Required:

• Azure ML Studio, AKS, Blob Storage, ADF, ADO Pipelines

• Model deployment & versioning via Azure ML

• MLflow for experiment tracking & model lifecycle management

• MLOps best practices — orchestration, CI/CD, model monitoring

• Strong Python skills (Linting, Black, dependency management)

• Drift detection & performance monitoring

• Docker-based deployment (good to have)

Job Details

- Job Title: Director of Engineering

- Industry: SAAS

- Function – Information Technology

- Experience Required: 9-14 years

- Working Days: 6 days

- Employment Type: Full Time

- Job Location: Bangalore

- CTC Range: Best in Industry

Preferred Skills: TypeScript, AWS, NodeJS, mongodb, React.js, WebGL, Three.js, AI/ML, Docker,nKubernetes

Criteria

Candidate must be having 9+ years of engineering experience, with 3u20134 years in technical leadership

Hands-on expertise with React/Next.js, Node.js/Python, and AWS.

Ability to design scalable architectures for high-performance systems.

Should have AI/ML deployment experience

Strong 3D graphics/WebGL/Three.js knowledge.

Candidates should be from SAAS/Software/IT Services based startups or scaleup companies only

Job Description

The Role:

Company is hiring a hands-on Director of Engineering who codes, architects systems, and builds teams. You’ll set the technical foundation, drive engineering excellence, and own the architecture of our AI, 3D, and XR platform.

This is not a pure management role - expect to spend 50–60% of your time writing code, solving deep technical problems, and owning mission-critical systems. As we scale, this role transitions into CTO, taking full ownership of technical vision and long-term strategy. 

What You’ll Own:

1. Technical Leadership & Architecture

● Architect company’s full-stack platform across frontend, backend, infrastructure, and AI.

● Scale core systems: VersaAI engine, rendering pipeline, AR deployment, analytics.

● Make decisions on stack, scalability patterns, architecture, and technical debt.

● Own design for high-performance 3D asset processing, real-time rendering, and ML deployment.

● Lead architectural discussions, design reviews, and set engineering standards.

2. Hands-On Development

● Write production-grade code across frontend, backend, APIs, and cloud infra.

● Build critical features and core system components independently.

● Debug complex systems and optimize performance end-to-end.

● Implement and optimize AI/ML pipelines for 3D generation, CV, and recognition.

● Build scalable backend services for large-scale asset processing and real-time pipelines.

● Develop WebGL/Three.js rendering and AR workflows.

3. Team Building & Engineering Management

● Hire and grow a team of 5–8 engineers initially (scaling to 15–20).

● Establish engineering culture, values, and best practices.

● Build career frameworks, performance systems, and growth plans.

● Conduct 1:1s, mentor engineers, and drive continuous improvement.

● Set up processes for agile execution, deployments, and incident response.

4. Product & Cross-Functional Collaboration

● Work with the founder and product team on roadmap, feasibility, and prioritization.

● Translate product requirements into technical execution plans.

● Collaborate with design for UX quality and technical alignment.

● Support sales and customer success with integrations and technical discussions.

● Contribute technical inputs to product strategy and customer-facing initiatives.

5. Engineering Operations & Infrastructure

● Own CI/CD, testing frameworks, deployments, and automation.

● Create monitoring, logging, and alerting setups for reliability.

● Manage AWS infrastructure with a focus on cost and performance.

● Build internal tools, documentation, and developer workflows.

● Ensure enterprise-grade security, compliance, and reliability.

Tech Stack:

1. Frontend

React.js, Next.js, TypeScript, WebGL, Three.js

2. Backend

Node.js, Python, Express/FastAPI, REST, GraphQL

3. AI/ML

PyTorch, TensorFlow, CV models, Stable Diffusion, LLMs, ML pipelines

4. 3D & Graphics

Three.js, WebGL, Babylon.js, glTF, USDZ, rendering optimization

5. Databases

PostgreSQL, MongoDB, Redis, vector databases

6. Cloud & Infra

AWS (EC2, S3, Lambda, SageMaker), Docker, Kubernetes CI/CD: GitHub Actions

Monitoring: Datadog, Sentry

What We’re Looking For:

1. Must-Haves

● 9+ years of engineering experience, with 3–4 years in technical leadership.

● Deep full-stack experience with strong system design fundamentals.

● Proven success building products from 0→1 in fast-paced environments.

● Hands-on expertise with React/Next.js, Node.js/Python, and AWS.

● Ability to design scalable architectures for high-performance systems.

● Strong people leadership with experience hiring and mentoring teams.

● Ready to code, review, design, and lead from the front.

● Startup mindset: fast execution, problem-solving, ownership.

2. Highly Desirable

● AI/ML deployment experience (CV, generative AI, 3D reconstruction).

● Strong 3D graphics/WebGL/Three.js knowledge.

● Experience with real-time systems, rendering optimizations, or large-scale pipelines.

● Background in B2B SaaS, XR, gaming, or immersive tech.

● Experience scaling engineering teams from 5 → 20+.

● Open-source contributions or technical content creation.

● Experience working closely with founders or executive leadership.

Why Company:

● Hard, meaningful engineering problems at the intersection of AI, 3D, XR, and web tech.

● Build from day zero – architecture, team, and culture.

● Path to CTO as the company scales.

● High autonomy to drive technical decisions.

● Direct founder collaboration on product vision.

● High ownership, high-growth environment.

● Backed by global leaders: Microsoft, Google, NVIDIA, AWS.

Location & Work Culture:

● Location: HSR Layout, Bengaluru

● Schedule: 6 days a week, (5 days-in-office, Saturdays WFH)

● Culture: High-intensity, high-integrity, engineering-first

● Team: Young, ambitious, technically strong

Experience: Experience: 10+ years of experience in software development & project management, with specialization in AI/ML

Qualification: B.E/B.Tech

Location: Pune

Role Overview

We are seeking a Head of AI Center of Excellence to execute our enterprise AI strategy. This role will be responsible for designing and delivering agentic AI systems and production-grade AI solutions, while driving rapid experimentation and pilot-ready proof-of-concepts in a fast-paced environment.

·    Required Qualifications:

• 10+ years of overall software development & management experience with 5+ years of hands-on experience in AI/ML system design and development
• Experience with technical project management; managing a team of AI/ML engineers across multiple projects
• Proven expertise in:
• Agentic AI architectures, LLM-based systems, and orchestration frameworks
• ML/DL model development, training, fine-tuning, and evaluation
• MLOps, model deployment, monitoring, and lifecycle management
• Strong proficiency in Python and modern AI/ML frameworks (e.g., LangGraph, PyTorch, TensorFlow, Hugging Face)
• Experience with cloud platforms and AI services (AWS, Azure, or GCP)
• Demonstrated ability to deliver pilot-ready AI PoCs quickly and effectively

Department

Product & Technology

Location

On-site | Prabhat Road, Pune

Experience

3-5 Years in a Data Engineering or Analytics Role

Domain

Fintech / Wealth Management — non-negotiable

Compensation

11-12 LPA Fixed + Performance Bonus

Growth

Title upgrade + salary revision at 12–18 months for strong performers

Why this role is different from most Data Engineer postings

You will work directly with the founding team on a live wealth management platform used by HNI and NRI clients. You will not spend years in a queue waiting to matter your work ships to production, your analysis influences product decisions, and you will guide junior teammates from day one. If you perform, a raise and title upgrade are on the table within 1218 months. This is the kind of early-team role that defines careers.

About Cambridge Wealth

Cambridge Wealth is a fast-growing, award-winning Financial Services and Fintech firm obsessed with quality and exceptional client service. We serve a high-profile clientele NRI, Mass Affluent, HNI, and ultra-HNI professionals and have received multiple awards from major Mutual Fund houses and BSE. We are past the zero-to-one stage and now focused on scaling our features and intelligence layer. You will be joining at exactly the right time.

What You Will Be Doing

This is a central, hands-on data engineering role at the intersection of financial analytics and applied ML. You will own the data pipelines and analytical models that power investment insights for wealth management clients transforming transaction data and portfolio information into measurable, actionable intelligence.

We are not looking for someone who just keeps the lights on. We want someone who looks at a working system and immediately sees how to make it 10x faster, cleaner, and smarter using AI and automation wherever possible.

Key Responsibilities:

Data Engineering & Pipelines

• Build and optimize PostgreSQL-based pipelines to process large volumes of investment transaction data.
• Design and maintain database schemas, foreign tables, and analytical structures for performance at scale.
• Write advanced SQL — window functions, stored procedures, query optimization, index design.
• Build Python automation scripts for data ingestion, transformation, and scheduled pipeline runs.
• Monitor AWS RDS workloads and troubleshoot performance issues proactively.

Financial Analytics & Modelling

• Develop analytical frameworks to evaluate client portfolios against benchmarks and category averages.
• Build data models covering mutual fund schemes, SIPs, redemptions, switches, and transfer lifecycles.
• Create materialized views and derived tables optimized for dashboards and internal reporting tools.
• Analyse client transaction history to surface patterns in investment behaviour and financial discipline.

Applied ML & AI-Driven Development

• Use Python (Pandas, NumPy, Scikit-learn) for trend analysis, forecasting, and predictive modelling.
• Implement classification or regression models to support financial pattern detection.
• Use AI tools — LLMs, Copilots — to accelerate ETL development, code quality, and data cleaning.
• Identify opportunities to automate repetitive data tasks and advocate for smarter tooling.

Data Quality & Governance

• Own data integrity end-to-end in a live, high-stakes financial environment.
• Build and maintain validation and cleaning protocols across all financial datasets.
• Maintain Excel models, Power Query workflows, and structured reporting outputs.

Collaboration & Junior Mentorship

• Work directly with Product, Investment Research, and Wealth Advisory teams.
• Translate open-ended business questions into structured queries and measurable outputs.
• Guide 1–2 junior trainees — review their work, set code quality standards, and help them grow.
• Present findings clearly to non-technical stakeholders — no jargon, just clarity.

Skills — What We Need vs. What Helps

Skill / Tool

Requirement

Must-Haves:

SQL & PostgreSQL (window functions, stored procedures, optimization)

Python — Pandas, NumPy for data processing and automation

ML fundamentals — classification or regression (Scikit-learn)

AWS RDS or equivalent cloud database experience

Financial domain knowledge — mutual funds, SIPs, portfolio concepts

Python data visualization — Matplotlib, Seaborn, or Plotly

Strong Advantage

Excel — Power Query, advanced modelling

Materialized views, query planning, index optimization

Experience with BI/dashboard tools

Good to Have

NoSQL databases

Prior fintech or wealth management startup experience

Financial Domain — Non-Negotiable

This is a wealth management platform. You must come in with a working understanding of:

• Mutual fund structures, scheme types, and NAV-based transactions
• Investment lifecycle — SIPs, Lump Sum, Redemptions, Switches, and STPs
• Portfolio allocation and benchmarking against indices (e.g. Nifty 50, category averages)
• How HNI/NRI clients interact with financial products differently from retail investors

You do not need to be a CFA. But if mutual funds and portfolio analytics are completely new territory, this role is not the right fit right now.

The Culture Fit — Read This Carefully

We are a small, fast-moving team. This is not a place where you wait for a ticket to arrive in your queue. The right person for this role:

• Has worked at a small startup before and is used to wearing multiple hats
• Finds broken or slow data systems genuinely irritating and fixes them without being asked
• Reaches for Python or an LLM when there is a repetitive task — automating is instinctive
• Is comfortable saying 'I don't know but I'll find out' and follows through independently
• Wants visibility and ownership, not just a well-defined job description
• Is looking for a role where strong performance is directly visible and rewarded

Growth Path — What Happens If You Perform

This is not a vague 'growth opportunity' pitch.

If you hit the bar in your first 12–18 months, you will receive a salary revision and a title upgrade to Senior Data Engineer or Lead Data Engineer depending on team expansion. As we scale our Data and AI team, this role is the natural stepping stone to a team lead position. You will also gain direct exposure to founding-team decision-making — the kind of access that is hard to get at larger companies.

Preferred Background

• 2–4 years in a data engineering or analytics role at a startup or small Fintech
• Experience in a live product environment where data errors have real consequences
• Exposure to portfolio analytics, investment research, or wealth management platforms
• Has mentored or reviewed code for at least one junior team member

Hiring Process

We respect your time. The process is direct and moves fast.

• Screening Questions — 5 minutes online
• Online Challenge — MCQ(Data, SQL, AWS, etc), and one applied ML or analytics problem, Communication Skills and Personality (focused, not trick questions)
• People Round — 30-minute video call, culture and communication
• Technical Deep-Dive — 1 hour in person, live financial data problems and your past work
• Founder's Interview — 1 hour in person, growth conversation and mutual fit
• Offer & Background Verification

We are looking for a highly skilled AI Platform Engineer to build and scale agentic AI capabilities across our product suite. You’ll work on multi‑agent systems, orchestration platforms, RAG pipelines, and real‑time AI services used in enterprise workflows.

🔹 Key Responsibilities

• Build and maintain AI platform services enabling agentic workflows
• Develop domain-specific agents (proposal generation, compliance, data analysis)
• Implement multi-agent orchestration using LangGraph and related frameworks
• Build APIs, SDKs, and integration layers for product teams
• Design and optimize RAG, GraphRAG, and knowledge ingestion pipelines
• Enhance orchestration platforms, WebSocket communication, and error recovery
• Optimize performance, latency (<3s), cost, and reliability of AI systems
• Collaborate closely with ML engineers and data scientists on models, prompts, and A/B testing

🔹 Required Skills & Experience

• 5+ years of software engineering experience (1–2+ years in AI/ML systems)
• Strong Python (FastAPI, async, LangChain/LangGraph)
• Experience with LLM APIs (OpenAI, Claude, Llama, Phi‑3)
• Hands-on RAG, embeddings, vector databases, and hybrid search
• React + TypeScript experience (WebSockets, hooks, real-time UI)
• Knowledge of multi-agent systems, prompt engineering, and orchestration patterns
• Solid backend fundamentals: REST APIs, databases, auth, testing, Git

🔹 Nice to Have

• MLOps exposure (prompt versioning, monitoring, A/B testing)
• Experience with semantic caching and context management
• Docker and cloud deployment basics

Senior Quality Engineer – AI Products

Fulltime

Remote

Requirements

● 3-7 years of experience in software quality engineering, preferably in SaaS environments with a platform or infrastructure focus.

● Strong demonstrated experience testing distributed systems, APIs, data pipelines, or cloud-based infrastructure.

● Experience designing and executing test plans for AI/ML systems, data pipelines, or shared platform services.

● Familiarity with AI/LLM infrastructure concepts such as retrieval-augmented generation (RAG), vector search, model routing, and observability.

● Strong demonstrated proficiency in Linux distributions and CLI-based testing, including log file analysis and other troubleshooting tasks.

● Experience with AWS or other major cloud platforms.

● Basic Python/Shell scripting knowledge with ability to edit existing scripts and create new automation for pipeline validation.

● Advanced skills with API and SQL testing methodologies.

● Familiarity with test management tools such as TestRail; experience with Qase is a plus.

● Demonstrated experience leveraging Version Control Systems with a focus on GitHub.

● Experience with testing tools: Jira, Sentry, DataDog.

● Strong understanding of Agile/Scrum methodologies.

● Proven track record of mentoring junior engineers and contributing to process improvements.

● Excellent analytical and problem-solving abilities.

● Strong communication skills with ability to present to both technical and non-technical stakeholders.

● Proficiency in English (C1-C2 level).

● Most importantly: The courage to be vocal about quality concerns, platform risks, and testing impediments.

Preferred Qualifications

● Experience with AI/ML evaluation frameworks or tools (e.g., LLM-as-judge, Ragas, custom eval harnesses).

● Hands-on experience with document parsing, OCR, or unstructured data pipelines.

● Experience with observability tooling (e.g., Datadog, Grafana, OpenTelemetry) from a QA perspective.

● Experience testing SaaS products in regulated industries (such as PCI-compliant).

● Basic understanding of containerization, Kubernetes, and CI/CD pipelines (Jenkins, CircleCI).

● Experience with microservice architectures and distributed systems.

● Knowledge of basic non-functional testing (security, performance) with emphasis on AI-specific concerns.

● Background in security or compliance testing for AI systems.

● Certifications such as ISTQB or CSTE.

● Experience working in legal technology, fintech, or professional services software.

● Familiarity with AI-assisted testing tools and leveraging LLMs as a productivity-boosting tool.

● Experience evaluating and implementing new QE tools and processes

About The Nexora Group Inc.

The Nexora Group Inc. is a technology-driven organization focused on developing intelligent software solutions using Artificial Intelligence, Machine Learning, and advanced data technologies. Our teams work on innovative projects involving data analysis, predictive modeling, automation systems, and AI-powered applications designed to solve real-world business problems.

We are seeking passionate and motivated Artificial Intelligence & Machine Learning Interns who want to gain hands-on experience working on practical AI development projects.

Internship Responsibilities

• Assist in developing and implementing machine learning models
• Work on data preprocessing, data analysis, and model training
• Support AI projects involving predictive analytics, automation, and intelligent systems
• Use Python libraries such as NumPy, Pandas, Scikit-learn, or TensorFlow
• Participate in testing and improving model performance
• Collaborate with development teams on AI-based applications
• Document project workflows and research findings

Required Skills

• Basic knowledge of Python programming
• Understanding of Machine Learning concepts
• Familiarity with data analysis and statistics
• Basic experience with libraries such as Pandas, NumPy, or Scikit-learn
• Interest in Artificial Intelligence technologies
• Good analytical and problem-solving skills

Preferred Qualifications

• Students or recent graduates in Computer Science, Artificial Intelligence, Data Science, or related fields
• Basic knowledge of Deep Learning or Neural Networks
• Familiarity with TensorFlow, PyTorch, or similar frameworks is a plus
• Understanding of data visualization tools is beneficial
• Experience with Git or version control systems is an advantage

What Interns Will Gain

• Hands-on experience working on AI and machine learning projects
• Exposure to real-world datasets and model development
• Opportunity to build a strong AI project portfolio
• Mentorship from experienced developers and data scientists
• Internship completion certificate based on performance and participation

About CK-12 Foundation

CK-12’s mission is to provide free access to open-source content and technology tools that empower both students and teachers to enhance learning across different styles, resources, competence levels, and circumstances.

To achieve this ambitious vision, CK-12 challenges the traditional education model by leveraging technology to revolutionize learning for students, teachers, and parents.

CK-12 operates as a non-profit organization so it can experiment with bold ideas and focus on doing the right thing for education. The organization is backed by Vinod Khosla, a renowned technology venture capitalist.

At CK-12, you’ll work in a dynamic, entrepreneurial, and innovative environment where passionate individuals collaborate to disrupt traditional education through technology.

Technology is at the heart of scaling education, and CK-12 builds solutions on a cloud-based (AWS) and AI-first platform delivering rich and interactive learning experiences.

If you are a great technologist who enjoys challenging the status quo and building innovative products, this could be the place for you.

Together, we aim to transform education globally.

Product Offerings

Flexi 2.0 – AI-Powered Student Tutor

https://www.flexi.org/

AI-Powered Teacher Assistant

https://www.ck12.org/pages/teacher-assistant/

Core Responsibilities

• Translate high-level directions and open-ended product ideas into deliverable ML projects and drive their completion.

• Architect and implement highly scalable ML solutions for systems such as multimodal information retrieval, conversational chatbots, recommender systems, and ranking systems.

• Own end-to-end product delivery from research and experimentation to production deployment.

• Work closely with cross-functional teams including Product, Engineering, DevOps, QA, and Content teams.

• Manage ML workflows involving data gathering, working with annotators, and collaborating with ML researchers.

• Extract and analyze large volumes of data to generate insights about student and teacher behavior based on platform usage.

• Design and build innovative ML-driven solutions that can improve learning experiences in the EdTech space.

• Apply statistical hypothesis testing and experimentation to evaluate and improve models.

• Continuously innovate and challenge the traditional approach to education through ML solutions.

Requirements

• Bachelor’s degree or higher in Computer Science or a related quantitative discipline, or equivalent practical experience.

• 4+ years of hands-on development experience with strong programming skills, preferably in Python.

• Expertise in deep learning approaches for NLP including transformer-based models, predictive modeling, search and recommendation systems, and autoregressive models.

• 2+ years of experience in NLP applications such as information retrieval, chatbots, summarization, or generative models.

• Proven experience building scalable ML applications on cloud infrastructure such as AWS, GCP, or Azure.

• Strong understanding of trade-offs between model architecture, deployment costs, and model accuracy.

• Ability to manage multiple tasks and collaborate effectively with geographically distributed teams.

• Up-to-date knowledge of advancements in NLP and computer vision and the ability to apply them in the education domain.

Technical Skills

• Python, PyTorch, TorchServe

• Pandas

• SQL and NoSQL databases such as MySQL, MongoDB, Redis, and Redshift

• Cloud infrastructure (AWS / GCP / Azure)

• Vector databases and search technologies such as Elasticsearch

• Linux

Nice to Have

• Familiarity with Reinforcement Learning

• Experience with Deep Knowledge Tracing

Job Title:

AI Native Operations Expert – Director / AVP / VP

Company: EOSGlobe

CTC: ₹24 – ₹36 LPA

Open Positions: 3

Experience: 12 – 18 Years

Joining: Immediate Joiners Preferred

Role Overview

EOSGlobe is transforming into an AI-First organization and is looking for an AI Native Operations Expert to lead this transformation. The role focuses on driving automation, process re-engineering, and AI adoption across BPM operations to improve efficiency, scalability, and business impact.

Key Responsibilities

Lead AI-driven transformation initiatives across BPM operations.

Re-engineer processes using Artificial Intelligence, Machine Learning, and automation tools.

Collaborate with leadership and strategy teams to implement AI-first operational models.

Define and track KPIs, productivity metrics, and financial impact of transformation initiatives.

Partner with internal teams and clients to demonstrate AI-driven efficiency and revenue growth.

Identify opportunities for process automation and digital adoption across operations.

Required Skills

Strong expertise in Artificial Intelligence (AI), Machine Learning (ML), and RPA.

Experience in process transformation and digital automation initiatives.

Deep understanding of BPM operations and service delivery models.

Strong leadership and stakeholder management skills.

Analytical mindset with ability to measure financial impact and operational KPIs.

Preferred Qualifications

Experience leading large-scale automation or AI transformation projects.

Exposure to BPM, consulting, or operations leadership roles.

Excellent communication and strategic thinking skills.

Job Title : Principal Backend Engineer (AI-Driven)

Experience : 10+ Years

Location : Chandigarh

Tech Stack : PHP, Node.js, Laravel, MySQL, MongoDB

Additional Requirement : Hands-on experience with AI technologies, APIs, or ML integrations

Role Overview :

We're looking for a Principal Backend Engineer (AI-Driven) to design and lead scalable backend systems while driving AI adoption across products.

The role involves integrating AI-powered features, architecting intelligent systems, and mentoring engineering teams on modern backend and AI implementation.

Key Responsibilities :

• Design and lead backend architecture using PHP (Laravel/CodeIgniter) and Node.js
• Build scalable microservices / modular backend systems
• Develop APIs and backend workflows for AI-driven features
• Integrate AI APIs (OpenAI, LangChain or similar frameworks)
• Work with LLMs, embeddings, vector databases, and AI pipelines
• Ensure performance, scalability, and security of backend systems
• Mentor engineering teams and drive backend + AI best practices

Requirements :

• 10+ years of backend development experience
• Strong expertise in PHP / Node.js, MySQL, MongoDB
• Hands-on experience integrating AI/ML APIs or AI-powered features
• Strong system design and architecture skills
• Experience leading engineering teams

Good to Have :

• Prompt engineering or AI cost optimization
• Exposure to MLOps / ML pipelines

What You’ll Do

● Partner with Product to spot high-leverage ML opportunities tied to business

metrics.

● Wrangle large structured and unstructured datasets; build reliable features and

data contracts.

● Build and ship models to:

○ Enhance customer experiences and personalization

○ Boost revenue via pricing/discount optimization

○ Power user-to-user discovery and ranking (matchmaking at scale)

○ Detect and block fraud/risk in real time

○ Score conversion/churn/acceptance propensity for targeted actions

● Collaborate with Engineering to productionize via APIs/CI/CD/Docker on AWS.

● Design and run A/B tests with guardrails.

● Build monitoring for model/data drift and business KPIs

What We’re Looking For

● 2–4 years of DS/ML experience in consumer internet / B2C products, with 7–8 models shipped to production end-to-end.

● Proven, hands-on success in at least two (preferably 3–4) of the following:

○ Recommender systems (retrieval + ranking, NDCG/Recall, online lift;

bandits a plus)

○ Fraud/risk detection (severe class imbalance, PR-AUC)

○ Pricing models (elasticity, demand curves, margin vs. win-rate trade-offs,

guardrails/simulation)

○ Propensity models (payment/churn)

● Programming: strong Python and SQL; solid git, Docker, CI/CD.

● Cloud and data: experience with AWS or GCP; familiarity with

warehouses/dashboards (Redshift/BigQuery, Looker/Tableau).

● ML breadth: recommender systems, NLP or user profiling, anomaly detection.

● Communication: clear storytelling with data; can align stakeholders and drive decisions.

About Us:

REConnect Energy’s GRIDConnect platform helps integrate and manage energy generation and consumption for 1000s of renewable energy assets and grid operators. We are currently serving customers across India, Bhutan and the Middle East with expansion planned in US and European markets.

We are headquartered in Central Bangalore with a team of 150+ and growing. You will join the Bangalore based Engineering team as a senior member and work at the intersection of Energy, Weather & Climate Sciences and AI. 

Responsibilities:

● Engineering - Take complete ownership of engineering stacks including Data Engineering and MLOps. Define and maintain software systems architecture for high availability 24x7 systems.

● Leadership - Lead a team of engineers and analysts managing engineering development as well as round the clock service delivery. Provide mentorship and technical guidance to team members and contribute towards their professional growth. Manage weekly and monthly reviews with team members and senior management.

● Product Development - Contribute towards new product development through engineering solutions to product requirements. Interact with cross-functional teams to bring forward a technology perspective.

● Operations - Manage delivery of critical services to power utilities with expectations of zero downtime. Take ownership for uninterrupted product uptime. 

Requirements:

● 4-5 years of experience building highly available systems

● 2-3 years experience leading a team of engineers and analysts

● Bachelors or Master’s degree in Computer Science, Software Engineering, Electrical Engineering or equivalent

● Proficient in python programming skills and expertise with data engineering and machine learning deployment

● Experience in databases including MySQL and NoSQL

● Experience in developing and maintaining critical and high availability systems will be given strong preference

● Experience in software design using design principles and architectural modeling.

● Experience working with AWS cloud platform.

● Strong analytical and data driven approach to problem solving 

Description

We are currently hiring for the position of Data Scientist/ Senior Machine Learning Engineer (6–7 years’ experience).

Please find the detailed Job Description attached for your reference. We are looking for candidates with strong experience in:

• Machine Learning model development
• Scalable data pipeline development (ETL/ELT)
• Python and SQL
• Cloud platforms such as Azure/AWS/Databricks
• ML deployment environments (SageMaker, Azure ML, etc.)

Kindly note:

• Location: Pune (Work From Office)
• Immediate joiners preferred

While sharing profiles, please ensure the following details are included:

• Current CTC
• Expected CTC
• Notice Period
• Current Location
• Confirmation on Pune WFO comfort

Must have skills

Machine Learning - 6 years

Python - 6 years

ETL(Extract, Transform, Load) - 6 years

SQL - 6 years

Azure - 6 years

Description

JOB DESCRIPTION – SENIOR ANALYST – DATA SCIENTIST 

Key Responsibilities ·       

Work with business stakeholders and cross-functional SMEs to deeply understand business context and key business questions·       

Advanced skills with statistical/programming in Python and data querying languages (e.g., SQL, Hadoop/Hive, Scala)·       

Solid understanding of time-series forecasting techniques·       

Good hands-on skills in both feature engineering and hyperparameter optimization·       

Able to write clean and tested code that can be maintained by other software engineers·       

Able to clearly summarize and communicate data analysis assumptions and results·       

Able to craft effective data pipelines to transform your analyses from offline to production systems·       

Self-motivated and a proactive problem solver who can work independently and in teams·       

Connects both externally and internally to understand industry trends, technology advances and outstanding processes or solutions·       

Is collaborative and engages (strategic & tactical. Able to influence without authority, handle complex issues and implement positive change·       

Work on multiple pillars of AI including cognitive engineering, conversational bots, and data science·       

Ensure that solutions exhibit high levels of performance, security, scalability, maintainability, repeatability, appropriate reusability, and reliability upon deployment ·       

Provide guidance and leadership to more junior data scientists, managing processes and flow of work, vetting designs, and mentoring team members to realize their full potential·       

Lead discussions at peer review and use interpersonal skills to positively influence decision making·       

Provide subject matter expertise in machine learning techniques, tools, and concepts; make impactful contributions to internal discussions on emerging practices·       

Facilitate cross-geography sharing of new ideas, learnings, and best-practices 

What We Are Looking For 

Required Qualifications ·       

Master's degree in a quantitative field such as Data Science, Statistics, Applied Mathematics or Bachelor's degree in engineering, computer science, or related field. ·       

4 – 6 years of total work experience as data scientist or analytical role, with at least 2-3 years of experience in time series forecasting·       

A combination of business focus, strong analytical and problem-solving skills, and programming knowledge to be able to quickly cycle hypothesis through the discovery phase of a project ·       

Strong experience in Time Series Forecasting and Demand Planning ·       

Advanced skills with statistical/programming software (e.g., R, Python) and data querying languages (e.g., SQL, Hadoop/Hive, Scala) ·       

Good hands-on skills in both feature engineering and hyperparameter optimization ·       

Experience producing high-quality code, tests, documentation·       

Understanding of descriptive and exploratory statistics, predictive modelling, evaluation metrics, decision trees, machine learning algorithms, optimization & forecasting techniques, and / or deep learning methodologies·       

Proficiency in statistical concepts and ML algorithms·       

Ability to lead, manage, build, and deliver customer business results through data scientists or professional services team·       

Ability to share ideas in a compelling manner, to clearly summarize and communicate data analysis assumptions and results·       

Self-motivated and a proactive problem solver who can work independently and in teams·       

Outstanding verbal and written communication skills with the ability to effectively advocate technical solutions to engineering and business teams 

Desired Qualifications ·      

Experience working in one or multiple supply chain functions (e.g., procurement, planning, manufacturing, quality, logistics) is strongly preferred ·       

Experience in applying AI/ML within a CPG or Healthcare business environment is strongly preferred ·       

Experience in creating CI/CD pipelines for deployment using Jenkins. ·       

Experience implementing MLOPs framework along with understanding of data security·       

Implementation on ML models·       

Exposure to visualization packages and Azure tech stack.  

Must have skills

Python - 2 years

Data Science - 4 years

SQL - 2 years

Machine Learning - 2 years

Nice to have skills

Data Analysis - 4 years

Time Series Forecasting - 2 years

Demand Planning - 2 years

Hadoop - 2 years

Statistical concepts - 2 years

Supply chain functions - 2 years