Data Science Engineer – GenAI / ML

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Job Title: Data Science Engineer – GenAI / ML

Location: Burbank, California, United States

Contract : w2 Contract

Note : Customer Location: Mason & Los Angels

JD :

Technical 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

· Knowledge of CI/CD pipelines and cloud deployment (Azure preferred)

· Experience with Vector DBs and/or MongoDB

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

Role Descriptions: Data Science Engineer (Customer Location Los Angels Mason)Role OverviewThe Data Science Engineer will develop scalable ML and Generative AI solutions| specializing in model training| document processing pipelines| and vector search implementations. Strong Python expertise and experience across modern ML and GenAI workflows are essential.Key Responsibilities- Develop and deploy Machine Learning and Generative AI solutions using Python- Design and refine prompt engineering strategies for LLM applications- Build document extraction| parsing| and chunking pipelines- Train| evaluate| and fine-tune ML models manage tagging and labeling workflows- Implement embedding generation and vector search solutions- Integrate ML models with vector databases and MongoDB- Ensure code quality| scalability| and production readinessRequired Qualifications- Expert-level proficiency in Python- Strong experience with model training| evaluation| and tagging workflows- Hands-on experience with document extraction and chunking techniques- Solid understanding of ML algorithms and Generative AI concepts- Experience with vector databases andor MongoDB

Essential Skills: Data Science Engineer (Customer Location Los Angels Mason)Role OverviewThe Data Science Engineer will develop scalable ML and Generative AI solutions| specializing in model training| document processing pipelines| and vector search implementations. Strong Python expertise and experience across modern ML and GenAI workflows are essential.Key Responsibilities- Develop and deploy Machine Learning and Generative AI solutions using Python- Design and refine prompt engineering strategies for LLM applications- Build document extraction| parsing| and chunking pipelines- Train| evaluate| and fine-tune ML models manage tagging and labeling workflows- Implement embedding generation and vector search solutions- Integrate ML models with vector databases and MongoDB- Ensure code quality| scalability| and production readinessRequired Qualifications- Expert-level proficiency in Python- Strong experience with model training| evaluation| and tagging workflows- Hands-on experience with document extraction and chunking techniques- Solid understanding of ML algorithms and Generative AI concepts- Experience with vector databases andor MongoDB

Desirable Skills:

Keyword:

Skills: Digital : Machine Learning~Digital : Mongo DB~Digital : Azure Machine Learning (ML)~Digital : Python for Data Science~AI & Gen AI - Products & Tools

Experience Required: 8-10

NOTE: Please share your updated resume to [email protected]