Data Science/Data Scientist

Tata Consultancy Services; Hyderabad, Bengaluru; On-site; INR 1,200,000 - 1,800,000; Full time

Job summary

Tata Consultancy Services is seeking an experienced ML Engineer to design, implement, and deploy production-ready ML models on large-scale datasets in Hyderabad. You will build AI agents, develop RAG pipelines, and optimize models for deployment using Azure ML Studio and related tools.

The role involves prompt engineering for supply chain workflows, working with LangChain or LlamaIndex, and delivering robust monitoring and testing in a production environment.

Qualifications

• Experience building ML models for production on large datasets.
• Strong Python programming with clean, production-grade code.
• Proficient in SQL; comfortable with large-volume data in Spark and Snowflake.
• Experience with Git for version control and collaboration.
• Familiarity with experiment tracking and model versioning (e.g., MLflow).
• Experience with time series forecasting and optimization modeling.
• Knowledge of feature engineering and statistical analysis on structured data.
• Proficient in deploying models to Azure ML / Azure services.

Responsibilities

• Build and deploy ML models on large-scale production datasets.
• Develop AI agents using Azure AI Studio and endpoints, including tool-use patterns.
• Design RAG pipelines with document ingestion, embedding and indexing, and LLM endpoints.
• Perform prompt engineering and chain-of-thought design for complex supply chain workflows.
• Work with orchestration tools like LangChain or LlamaIndex for end-to-end pipelines.
• Deliver production-ready models with proper testing, validation, and monitoring; create quick UIs with Streamlit or Gradio.

Skills

Python

ML

Production ML

SQL

Spark

Snowflake

Git

MLflow

Time series

Optimization

Feature engineering

API usage

Tools

Azure Machine Learning

Azure AI Studio

Azure OpenAI Service

LangChain

LlamaIndex

Streamlit

Gradio

Spark

Job description

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