ML Engineer

Tata Consultancy Services; Hyderabad; On-site; INR 400,000 - 900,000; Full time

Job summary

TCS Data & Analytics seeks senior AI engineers to design and optimize generative AI systems. You will collaborate with data scientists to prepare large datasets and deploy models in scalable production environments. The role emphasizes MLOps practices, model monitoring, and continuous improvement.

You will mentor junior engineers and contribute to architecture decisions across cloud platforms (AWS/Azure/GCP), ensuring robust, AI-ready ecosystems for business transformation.

Qualifications

• 7+ years of professional AI experience.
• 3+ years in AI/Gen AI projects and production systems.
• Strong knowledge of AI methodologies including generative models, ML, RL, and NLP.

Responsibilities

• Design, implement, and optimize generative AI architectures and models.
• Collaborate with data scientists to collect, preprocess, and manage large datasets for training.
• Collaborate with cross-functional teams to deploy AI models in production environments.
• Fine-tune models to improve accuracy, efficiency, and scalability.
• Provide technical guidance and mentorship to junior engineers.

Skills

Gen AI

NLP

ML

Reinforcement Learning

AI methods

Model design

AI model optimization

MLOps

CI/CD

Cloud platforms

Python

TensorFlow

PyTorch

Keras

LangChain

LangGraph

GA Dev Kit

RAG

Tools

TensorFlow

PyTorch

Keras

LangChain

LangGraph

MLFlow

GA Dev Kit

AWS

Azure

GCP

Job description

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.

Location - Pan India

Experience - 10+ 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.>