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: $95,000 - $135,000 per year

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 & 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