Top Artificial Intelligence Jobs in Chennai

Create brand videos combining traditional editing and generative AI for image, motion, and voice. Conceptualize, edit, and finalize deliverables using Adobe Creative Cloud while collaborating with marketing and design teams and staying current on AI tools.

Lead design, development, and deployment of production-grade LLM and RAG-based AI solutions. Improve retrieval performance, build automated evaluation and validation frameworks, instrument pgvector retrieval KPIs, integrate metrics into CI/CD, and mentor mid-level engineers while driving technical reviews and best practices.

Design and build enterprise-scale AI search and retrieval systems using Azure AI Search and Azure OpenAI. Implement RAG/vector search, embeddings, prompt engineering, secure document-level access controls, scalable backend services, and observability to improve relevance, accuracy, and latency. Mentor engineers and drive architecture for secure, compliant enterprise RAG platforms.

Manage and grow an India-based AI Development team to deliver enterprise agent applications. Translate product priorities into sprints, partner with the Director of AI on roadmap and technical execution, establish async-first delivery rhythms across US/India, handle India operations (hiring, performance, compensation), coach on modern programming practices, and unblock work through cross-team relationships.

Lead and align Engineering, ML, and Analytics to deliver scalable, reliable production AI and data systems. Own technical direction, architecture, MLOps, and platform reliability while partnering with Product, Sales, and Customers to ensure engineering work maps to measurable business outcomes.

Build and optimize Angular front-end features that integrate AI/ML models and APIs. Collaborate with data scientists, backend engineers, and designers to implement responsive, secure UI components, visualize model outputs, and deploy AI-powered web functionality.

Hands-on pre-sales technical lead who designs AI/data solution architectures, builds POCs and reusable assets, authors RFP responses, and transitions solutions to delivery across cloud data platforms, ETL/ELT, and applied ML to drive client outcomes.

Build and deploy production-grade generative AI applications: design multi-agent systems and LangGraph workflows, implement advanced RAG with vector DBs, fine-tune and host LLMs, develop scalable FastAPI backends, optimize latency/cost, and containerize services for production.

Design, develop, and deploy machine learning and deep learning models; build end-to-end ML pipelines including preprocessing, training, evaluation, and deployment; perform feature engineering on large datasets; deploy and monitor models on cloud platforms; collaborate with cross-functional teams to integrate AI solutions and retrain models as needed.

Design, develop, fine-tune, and deploy generative AI models (LLMs, diffusion, VAEs). Build data pipelines, APIs, and integrate AI into production while improving performance and collaborating with cross-functional teams.

Design, build, and scale production Generative AI systems: multi-agent workflows, advanced RAG pipelines, model fine-tuning and quantization, LLM integration and swapping, high-performance FastAPI backends, vector search and retrieval, containerized deployment, and monitoring for latency, cost, and reliability.

Lead design and architecture of Generative AI solutions on Azure and OpenAI, build end-to-end data pipelines and cloud infrastructure, produce solution blueprints, collaborate with stakeholders, and implement data preprocessing, API deployment, monitoring, and analytics delivery.

Design, develop, and deploy Gen AI solutions (chatbots, IVR, banking) using LLMs, Langchain/Haystack, vector/graph DBs, and speech-to-text. Build semantic search, embeddings, and scalable systems; collaborate cross-functionally and document work.

Design, fine-tune, and deploy generative AI models (LLMs, diffusion, VAEs). Build data pipelines and APIs, integrate AI into production, optimize model performance and latency, and collaborate with cross-functional teams to deliver AI-powered solutions.

Evaluate AI coding agents end-to-end, judging usefulness, high-level correctness, engineering judgment, and quality of explanations. Provide opinionated feedback, distinguish response quality levels, and help define standards for great AI-developer interactions. Participate in take-home evaluation and interview as part of a rolling, project-based engagement.

Design, train, optimize, and deploy production computer vision and visual search models for mobile and cloud. Build scalable training pipelines, model versioning, evaluation, and inference services. Improve robustness, mobile performance, and retrieval quality while collaborating with mobile, backend, and product teams to integrate and operationalize ML solutions.

Manage and maintain Eloqua/Salesforce MarTech architecture, integrations, data quality, targeting, lead scoring, and campaign tracking. Design and implement AI-augmented operational workflows, build AI-ready marketing data layers, document system architecture, and collaborate with marketing, revenue ops, and IT to ensure scalable, automated campaign execution.

Seeking a Senior Data Scientist skilled in GenAI/LLMs to design and implement solutions for enterprise, conducting research and mentoring others.

Design and manage AI architectures using AWS, develop cloud-native solutions, mentor teams, ensure compliance, and evaluate emerging technologies.

Manage Alation's generative engine optimization and visibility strategies, optimizing content for AI models while driving measurable marketing outcomes.

Build AI-assisted workflows and tool-using agents for semiconductor engineering automation: connect agents to platform APIs and data, create knowledge-ingestion pipelines, design evaluation datasets and tests, develop reusable workflow templates, and integrate agents with real tools producing traceable results.

Design and implement optimization and planning algorithms for engineering automation. Build constraint-handling logic, benchmarking and visualization tools, define metrics, run applied ML experiments for ranking and learned cost functions, and collaborate with platform, AI, and domain engineers to productionize algorithmic solutions.

As an AI Intern at Valeo, you'll support innovative projects aimed at developing environmentally friendly mobility solutions while working in a diverse, global team.

The AI Architect - Manager role involves defining enterprise AI solutions, guiding teams from concept to production, and collaborating across various engineering and business teams to enhance AI delivery foundations.

Lead strategy and development of AI/ML engineering solutions, enhancing decision-making and automation across the enterprise. Oversee advanced analytics and mentoring of data science teams.