Data Science Engineer – GenAI / ML

Job Title

Data Science Engineer – GenAI / ML

Location

Burbank, California, United States

Contract

w2 Contract

Note

Customer Location: Mason & Los Angeles

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 Overview The 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 readiness

Required 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 Overview The 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 readiness

Required 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 LearningDigital : Mongo DBDigital : Azure Machine Learning (ML)Digital : Python for Data ScienceAI & Gen AI - Products & Tools

Experience Required

8-10 years

NOTE

Please share your updated resume to c2c@galaxyitech.com