Data Science-Walkin Drive-31st Oct

Tata Consultancy Services Limited; Hyderabad; On-site; INR 1,800,000 - 2,800,000; Full time

Job summary

Tata Consultancy Services Limited is seeking an ML Engineer to develop production-grade ML models on large datasets, focusing on Pyhton/Spark/Snowflake, and to build AI agents using Azure AI Studio and OpenAI services. The role involves RAG pipelines, prompt engineering, and orchestration with LangChain or LlamaIndex.

Responsibilities include delivering production-ready models with testing and monitoring, plus lightweight UI prototyping with Streamlit/Gradio for demos and stakeholder reviews.

Qualifications

• Experience building ML models for production on large-scale datasets.
• Strong Python coding with production-quality, well-structured code.
• Proficiency in SQL; experience with large-volume data in Spark/Snowflake.
• Experience with Git for version control and collaboration.
• Familiarity with MLflow for experiment tracking and model versioning.

Responsibilities

• Develop ML models for production deployment on large-scale datasets.
• Build AI agents and LLM-based solutions using Azure AI Studio and Endpoints.
• Create RAG pipelines: document ingestion, embedding/indexing, and response generation.
• Design prompts and chain-of-thought strategies for complex supply chain workflows.
• Utilize LangChain or LlamaIndex for orchestration and tooling.

Skills

Python

SQL

Spark

Snowflake

Git

MLflow

Experiment tracking

Model deployment

Tools

Azure ML

Azure AI Studio

Azure OpenAI Service

LangChain

LlamaIndex

Streamlit/Gradio

Job description

Role & responsibilities

equired

Core Programming & Tools

• Hands-on experience building and deploying ML models on large-scale production datasets
• Strong programming proficiency in Python with production-quality, well-structured code
• Proficient in SQL; experience working with large-volume datasets in Spark and/or Snowflake
• Experience with Git for version control, code review, and collaboration
• Familiarity with experiment tracking and model versioning (e.g., MLflow)

Classical ML & Statistical Modeling

• Time series forecasting (ARIMA, Prophet, deep learning approaches)
• Optimization modeling (linear programming, mixed-integer programming)
• Classification, regression, clustering, and ensemble methods
• Feature engineering, data wrangling, and statistical analysis on structured data

LLM Application & AI Agent Development

• AI Agent development: experience building agentic frameworks using Azure AI Studio and Azure model endpoints, including tool-use patterns and multi-step orchestration
• RAG pipeline development: document ingestion/chunking, vector embedding/indexing (Azure AI Search), and response generation using LLM endpoints
• Prompt engineering and chain-of-thought design for complex supply chain workflows
• Experience with orchestration frameworks like LangChain or LlamaIndex

Azure & Production Delivery

• Familiar with core Azure resources: Azure Machine Learning, Azure AI Studio, Azure OpenAI Service, and Azure storage/compute
• Experience delivering production-ready models with proper testing, validation, and monitoring
• Basic UI skills (Streamlit or Gradio) for quick prototyping and demos