Data Science Senior Engineer
Tata Consultancy Services, Los Angeles, CA, United States
Must Have Technical/Functional Skills
• Advanced Python development for ML/AI workloads
• Endtoend ML lifecycle: model training, evaluation, finetuning, 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
• Productiongrade ML engineering: scalable, maintainable, and deploymentready code
Python, Large Language Models (LLMs) (via LLMbased 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 $110000 -$150,000 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
• Advanced Python development for ML/AI workloads
• Endtoend ML lifecycle: model training, evaluation, finetuning, 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
• Productiongrade ML engineering: scalable, maintainable, and deploymentready code
Python, Large Language Models (LLMs) (via LLMbased 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 $110000 -$150,000 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