Walk-in | Data Science

Tata Consultancy Services Limited; Hyderabad; Vor Ort; INR 1.800.000 - 3.200.000; Vollzeit

Zusammenfassung

Tata Consultancy Services Limited is seeking a senior ML engineer with 6-10 years of hands-on experience to design, build, and deploy production-grade ML models on large datasets. The role emphasizes Python/Spark/Snowflake, MLflow, and end-to-end pipelines, including ARIMA/Prophet forecasting, optimization, and AI agent development using Azure AI Studio.

You'll work on RAG pipelines, document ingestion, embeddings, and LangChain/LlamaIndex orchestration to deliver scalable solutions.

Qualifikationen

• 6–10 years hands-on ML production experience.
• Proficient Python with production-quality, well-structured code.
• Proficient in SQL; experience 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).
• Time series forecasting using ARIMA, Prophet, or DL approaches.
• Experience with optimization modeling (linear programming, MILP).
• Knowledge of ML algorithms: classification, regression, clustering, and ensembles.
• AI Agent development using Azure AI Studio and model endpoints.
• RAG pipeline development: ingestion, embeddings, indexing, and Azure Search.
• Prompt engineering and chain-of-thought design for complex workflows.
• Experience with LangChain or LlamaIndex.

Aufgaben

• Build and deploy ML models on large-scale production datasets.
• Collaborate on data pipelines and feature engineering for production models.
• Implement time series forecasting and evaluation pipelines.
• Develop AI agents using Azure AI Studio and model endpoints.
• Create RAG pipelines with document ingestion, embeddings, and search integration.
• Design prompts and chain-of-thought strategies for LLM-driven workflows.
• Integrate orchestration tools like LangChain or LlamaIndex for end-to-end solutions.

Kenntnisse

Python programming

SQL

Git

MLflow

Time series forecasting

Optimization modeling

Feature engineering

Azure AI Studio

Azure model endpoints

LangChain / LlamaIndex

RAG pipelines

LLM workflows

Spark

Snowflake

Tools

Spark

Snowflake

Git

MLflow

Azure AI Studio

Azure Cognitive Search

LangChain

Jobbeschreibung

6-10 years 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)

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

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