Live opening · Posted 6 days ago
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About the Unit:
TCS Data & Analytics is powering the AI revolution by transforming data into a strategic enterprise asset. Built on the philosophy of Smart Data for Smarter AI, it enables organizations to create intelligent, AI-ready ecosystems that accelerate innovation, unlock new value, and drive business transformation at scale. As AI reshapes industries, TCS is helping businesses turn data into their most powerful competitive advantage.
Job Title: ML Engineer
Work Location: Pan India
Experience: 10-15 years
Required Skills:
< · 7+ years of experience
. 3+ years in AI/Gen AI
. 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
. 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
. Fine-tune and optimize AI models for specific applications, focusing on improving accuracy, efficiency, and scalability
. Experience of cloud-based platforms (e.g., AWS, Azure, GCP) to develop and deploy scalable AI solutions, ensuring high availability and performance
. Implement MLOps, LLMOps, AgentOps best practices for continuous integration and deployment (CI/CD) of AI models, including monitoring, logging, and version control
. Proficiency in programming languages such as Python, .Net or Java, with experience in relevant libraries and frameworks (e.g., TensorFlow, PyTorch, Keras)
. Knowledge of LangChain, Phoenix, MLFlow, LangGraph, Google Agent Development Kit
. Knowledge of implementing AI solutions using Agentic approach, Retrieval-Augmented Generation (RAG), Model Context Protocol (MCP), etc.
· Experience in developing and deploying AI/Gen AI based systems in production
. Provide technical guidance and mentorship to junior engineers and team members.>
< - Data Preparation and Preprocessing
- Model Development and Training
- Model Deployment and Integration
- MLOps, LLMOps, AgentOps and Continuous Monitoring
- Collaboration and Optimization >
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