Data Science Engineer – GenAI / ML

Hi, Everyone • • • • • • W2 CONTRACT ONLY • • • W2 CONTRACT ONLY • • • W2 CONTRACT ONLY • • • • • • 100% Closure & Long-term project, Immediate Interview Surely 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 c2c@galaxyitech.com