Top Machine Learning Jobs in Chennai

Build data-driven solutions and BI using Python, Power BI, and SQL. Implement DevOps pipelines with GitHub Actions/Azure DevOps, deploy on Azure/AWS, integrate APIs, apply unit testing and automation, and collaborate in Agile/Scrum with global teams. Support solution design, effort estimates, and use ML/DL/LLMs for intelligent features.

Implement and evaluate machine learning models, manage model training and deployment, design data pipelines, build integrations and low-code solutions using AI-assisted tools, and ensure data governance and security while partnering with legal and technology stakeholders.

Lead design and implementation of agentic GenAI solutions. Build prototypes, production services, RAG pipelines, LLM orchestration, and cloud-native deployments on Azure. Drive LLMOps, evaluation, performance optimization, DevOps/MLOps practices, and mentor engineering teams to deliver secure, scalable conversational and agent-based AI systems.

Design and implement scalable backend services, lead full software lifecycle, write design docs, mentor engineers, collaborate cross-functionally, improve performance and quality, and integrate AI tools to boost development productivity.

Lead AI opportunity discovery, prioritize use cases, design AI-enabled product strategies and implementation roadmaps. Translate operational challenges into feasible AI solutions, assess data readiness, define high-level architectures, build ROI models, develop governance for responsible AI, and drive stakeholder engagement and field-based implementation (50–80% travel).

Design, build, and operate production-grade GenAI/LLM systems: RAG pipelines, agentic multi-agent orchestration, vector DBs, LLM integrations, observability, PII redaction, and deployment using AWS Bedrock, FastAPI, Docker and monitoring tools. Collaborate on architecture docs and CI/AI evaluation frameworks.

Lead product strategy and roadmap for AI-powered Digital Assistant across quote-to-cash workflows. Translate business needs into product requirements, collaborate with data scientists, ML engineers, designers and software teams, prioritize features, monitor metrics, ensure ethical AI use, drive execution from ideation to launch, and communicate with stakeholders through demos and training to improve support efficiency and customer satisfaction.

Lead product strategy and roadmap for AI-powered Digital Assistant across quote-to-cash workflows. Translate business needs into requirements, collaborate with ML and engineering teams, prioritize features, monitor performance, and ensure ethical AI. Drive cross-functional alignment, build business cases, and deliver demos to stakeholders.

Support delivery of APC projects: analyze plant data, develop and configure APC applications, assist commissioning and troubleshooting, implement IIoT and digital solutions, and provide post-commissioning support while collaborating with site teams.

Lead AI enablement for data, reporting, and analytics within Client Protection. Identify and validate AI use cases, run proofs of concept, pilot solutions, build user guides, present findings, and partner with stakeholders to accelerate AI adoption while ensuring governance and compliance.

Design, develop and automate end-to-end test suites for cloud-based networking products. Execute functional, integration, performance and scale tests; review customer issues; collaborate with product, development and CloudOps; perform API and UI automation; and validate networking, security and virtualization features.

Lead Flutter platform architecture to power thousands of dynamically rendered mobile apps. Design modular widget libraries, state management, native integrations, performance optimizations, CI/CD and testing frameworks. Build real-time social commerce, personalization, offline-first sync, analytics, and developer tools while mentoring teams and driving Flutter ecosystem adoption.

Lead R&D and deliver end-to-end LLM/ML solutions for text extraction, analysis and recommendation engines. Develop, fine-tune, and deploy ML/LLM models for matching customers with relevant content, ensure scalable cloud integration (AWS), collaborate with engineering and product, communicate results via visualizations/reports, and mentor junior engineers to drive continuous improvement and measurable business outcomes.

Serve as site compliance lead for Chennai (supporting Bangalore), advising senior leaders on privacy, AI governance, and technology risk. Design and deliver compliance programmes, manage DPIAs, audits, investigations, third-party and cloud risk assessments, and embed privacy-by-design across technology teams. Partner with global privacy/DPO, HR, finance and assurance to monitor, report, and remediate compliance gaps.

Lead site-level compliance and privacy for Chennai (with Bangalore support). Advise senior leaders, design compliance programmes, manage risk, audits, investigations, and privacy-by-design for technology and AI projects. Coordinate with global privacy, Assurance, HR, Procurement, and third-party assessments to ensure regulatory alignment and safe deployment of data-driven solutions.

The Staff Product Manager will lead product backlog for a Scrum team, collaborating closely with engineering and AI teams while driving customer outcomes and improvements through analytics and integration solutions.

Research and develop domain-specific LLMs and generative models for materials science: pretraining, fine-tuning, alignment (e.g., RLHF), evaluation, dataset curation, and benchmark creation. Collaborate with scientists and engineers to apply generative AI to discovery and hardware design, publish research, and mentor junior team members.

The Operational Excellence Manager drives performance improvements, mentors site teams, implements lean principles, and integrates digitization strategies to achieve operational excellence.

The role focuses on evaluating Generative AI solutions, ensuring quality standards, mentoring team members, and improving data models in an academic research setting.

Design and implement a unified orchestration layer coordinating vendor and internal LLMs and human agents. Build production-grade Python services, drive ML projects from design to delivery, ensure secure, scalable AI-enabled customer experiences, and collaborate across teams to meet security, compliance, and performance standards.

As an ML Engineer, you will design, experiment, and deploy AI/ML models, evaluate their performance, and leverage Python and SQL.

Lead algorithm design and development for wafer inspection products, delivering image processing, computer vision, and machine learning solutions. Define performance requirements, mentor engineers, support system integration, validate and deploy algorithms, and ensure software quality and reliability.

Design, clean, analyze, and visualize data using SQL and Python; build Tableau dashboards; apply statistics and basic ML/DS concepts; follow software/data-engineering practices (version control, unit testing, high-performance code); work with structured and unstructured data and cloud environments.

Lead design, develop, test, and deploy scalable Java/Spring Boot cloud-native applications on AWS/Azure. Integrate AI/ML, build full-stack solutions with ReactJS, enforce code quality, mentor engineers, champion DevOps/security practices (Kubernetes, Docker, CI/CD, Git), and design compliant KYC/AML banking solutions.

Design and implement AI models, operationalize ML models, develop CI/CD pipelines for ML workflows, and provide technical guidance while ensuring data security compliance.