Data Science Engineer

Must Have Technical/Functional Skills

• Advanced Python development for ML/AI workloads
• End‑to‑end ML lifecycle: model training, evaluation, fine‑tuning, and labeling/tagging workflows
• Generative AI systems design, including LLM-based application development
• Prompt engineering optimization for large language models
• Document AI pipelines: OCR/extraction, parsing, normalization, and text chunking for structured & unstructured data
• Embedding generation pipelines for semantic search and retrieval
• Vector similarity search implementation using vector databases
• ML model integration with Vector DBs and MongoDB
• Production‑grade ML engineering: scalable, maintainable, and deployment‑ready code Python, Large Language Models (LLMs) (via LLM‑based applications), Vector Databases, MongoDB Roles & Responsibilities We are seeking a highly skilled Data Science Engineer to design and develop scalable ML and Generative AI solutions.

The ideal candidate will have deep expertise in Python, hands-on experience in model training, document processing pipelines, and strong knowledge of vector databases and modern ML/GenAI frameworks.

Strong fit if the candidate:

• Has expert level Python skills
• Has hands on experience building ML/GenAI systems, not just theoretical knowledge
• Has worked on end to end ML pipelines (data → model → deployment)
• Has experience with document AI, embeddings, and vector search
• Thinks like an engineer (scalable, maintainable, production ready code) Likely not a fit if the candidate is:
• Primarily a BI / reporting analyst
• Focused only on statistical modeling or academic research
• Lacking experience with deployment, pipelines, or GenAI systems Key Responsibilities
• Develop and deploy machine learning and GenAI solutions using Python
• Design and optimize prompt engineering strategies for LLM-based applications
• Build document extraction, parsing, and chunking pipelines for structured and unstructured data
• Train, evaluate, and fine-tune ML models; manage tagging and labeling workflows
• Implement embedding generation and vector search solutions
• Integrate ML models with Vector DBs and MongoDB
• Ensure code quality, scalability, and production readiness Salary Range $95000 -$135,000 years

TCS Employee Benefits Summary:

Discretionary Annual Incentive.

Comprehensive Medical Coverage:

Medical & Health, Dental & Vision, Disability Planning & Insurance, Pet Insurance Plans.

Family Support:

Maternal & Parental Leaves.

Insurance Options:

Auto & Home Insurance, Identity Theft Protection.

Convenience & Professional Growth:

Commuter Benefits & Certification & amp; Training Reimbursement.

Time Off:

Vacation, Time Off, Sick Leave & Holidays.

Legal & Financial Assistance:

Legal Assistance, 401K Plan, Performance Bonus, College Fund, Student Loan Refinancing. #LI-SP1