Senior Data Scientist

Indore, Raipur, IN Until 9/21/2026 8+ years exp H-1B sponsor history First posted July 23, 2026 Last posted July 23, 2026
Job description

Self-motivated Engineer with a solid grasp of AI/ML fundamentals and a relentless drive for innovation. This role requires an agile builder who can bridge the gap between model research and production-grade software with a product-focused mindset.

Key Responsibilities

  • Implement high-performance systems leveraging LLMs, Generative AI, and traditional ML to solve enterprise-scale problems.
  • Build and maintain RAG (Retrieval-Augmented Generation) workflows and data pipelines using Python and vector databases.
  • Refine model outputs through prompt engineering, fine-tuning, and latency optimization.
  • Write modular, scalable code and integrate AI services into cloud ecosystems (AWS, Azure, or GCP).
  • Rapidly integrate emerging frameworks like LangChain, LlamaIndex, and Hugging Face into production workflows.
  • Implement automated testing, model monitoring, and "golden datasets" to ensure reliability and safety.

Experience Required

  • 8+ years of hands-on experience in GenAI, Agentic AI, MCP & LLM’s
  • Experience in deploying models in production environments.

Why Join Us?

  • Work in an innovative environment with the business that is shaping the future of data migration.
  • Be part of a dynamic, high-growth environment at NucleusTeq.
  • Competitive salary and comprehensive benefits package.
About this role

Summary

Develop and deploy AI/ML models, build data pipelines, integrate frameworks, ensure reliability.

Job title

Senior Data Scientist

Experience level

8+ years

Minimum experience

8+ years exp

Industry

software

Location requirements

Indore, Raipur, IN; remote work not specified

Salary

Not specified

Visa sponsorship

H-1B sponsor history

Management role

No

Skills & keywords

Required skills

PythonLLMsModel deploymentAI frameworkscloud ecosystems

Preferred skills

None specified

Specializations

AI/MLLLMsGenerative AImodel deploymentdata pipelines
Locations

Structured locations inferred from the posting.

Unknown location

Work arrangement unknown