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Data Scientist

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Hybrid

Data Scientist

Elabs Infotech

Data Scientist

Skills

Data EngineeringPythonDatabricksData AnalysisMachine LearningAI

2 months ago

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Important information


Contract type:

Permanent

Location:

Chennai, Tamil Nadu, India

Work mode:

Hybrid

Published on:

18 August 2026

What they need


We are looking for a talented Data Scientist / Generative AI Engineer with strong hands-on experience in Generative AI, `, Python, RAG, LangChain/LangGraph, and Databricks. The ideal candidate will design and develop intelligent AI solutions using Large Language Models (LLMs), retrieval-augmented generation, AI agents, and modern data engineering platforms.

The role involves working closely with data scientists, engineers, and business stakeholders to build scalable, production-ready AI applications that solve complex business problems.

Key Responsibilities

  • Design, develop, and deploy Generative AI and Agentic AI applications using LLMs and modern AI frameworks.
  • Build RAG (Retrieval-Augmented Generation) pipelines for enterprise knowledge retrieval and question-answering use cases.
  • Develop intelligent, multi-step AI agents and agentic workflows using LangGraph and LangChain.
  • Develop high-quality, maintainable Python code for AI/ML applications and data pipelines.
  • Work with LLMs, prompt engineering, embeddings, vector databases, and model evaluation techniques.
  • Design solutions for document ingestion, chunking, embedding generation, semantic search, retrieval, and response generation.
  • Build and optimize AI workflows involving multiple tools, agents, APIs, and enterprise data sources.
  • Leverage Databricks for data processing, analytics, ML/AI development, and production workloads.
  • Collaborate with data engineering teams to integrate structured and unstructured enterprise data into AI solutions.
  • Implement evaluation, monitoring, observability, and performance optimization for GenAI applications.
  • Participate in architecture, design, development, testing, deployment, and production support of AI solutions.
  • Stay current with emerging developments in LLMs, Agentic AI, RAG, AI orchestration, and enterprise GenAI.

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