[Skip to main content](#main-content) [OpenNash Jobs](https://jobs.opennash.com/) [Hiring report](/reports/hiring/) · [All Tata Consultancy Services jobs](https://jobs.opennash.com/companies/tata-consultancy-services/) · [Search jobs](/search/) Tata Consultancy Services · Chennai # AI ML Developer Chennai Software Engineering Last seen on Tata Consultancy Services’s official careers site on August 1, 2026; it may have closed since. [Apply on Tata Consultancy Services’s careers site →](https://ibegin.tcsapps.com/candidate/next/en-IN/jobs/424763J) [OpenNash Jobs](https://jobs.opennash.com/) / [Tata Consultancy Services](https://jobs.opennash.com/companies/tata-consultancy-services/) / AI ML Developer ## Job description ### Role AI /ML Engineer Experience: 4 to 15 years of experience (2+ years in AI/Gen AI is must). ### Locations PAN India (Metro Cities) ### Required Skills Degree in computer science, artificial intelligence, or IT. Strong knowledge of AI methodologies, including generative models, machine learning (ML), reinforcement learning, and natural language processing (NLP). Design, implement, and optimize generative AI architectures and models. Build Agentic AI solutions using LLMs, including tool/function calling, Model Context Protocol (MCP), memory, workflows, and orchestration. Collaborate with data scientists and analysts to collect, preprocess, and manage large datasets, ensuring data quality and integrity for model training. Collaborate with cross-functional teams to integrate AI models into production environments, ensuring seamless deployment and operational efficiency. Experience of cloud-based platforms (e.g., AWS, Azure, GCP) to develop and deploy scalable AI solutions, ensuring high availability and performance. Strong hands-on experience in end-to-end AI/ML engineering, including data preprocessing, feature engineering, model training, evaluation, and optimization for production use cases. Proficiency in programming languages such as Python,.Net or Java, with experience in relevant libraries and frameworks (e.g., TensorFlow, PyTorch, Keras).