Data Science Engineer / Los Angeles / Fully Onsite / Python / LLMs / MongoDB
Motion Recruitment · Los Angeles, CA · 3 wk ago
On-siteInformation Technology$50–$70/hrContract
About the role
Los Angeles, California
Contract
$50/hr - $70/hr
Contract duration: 6 months with possible extension
Responsibilities
- 40% Python, Model Development, and Training
- 25% Generative AI, Prompt Engineering, and LLM Applications
- 20% Document AI, Embeddings & Vector DB Integration
- 15% CI/CD, Production Deployment, Code Quality
70% Hands-on ML/GenAI Engineering
20% Team Collaboration & Feature Development
10% Technical Planning, Documentation & Code Review
Requirements
- Advanced Python development for ML/AI workloads
- Experience with the full ML lifecycle: model training, evaluation, fine-tuning, and labeling/tagging
- Generative AI systems design and LLM-based application development
- Prompt engineering for large language models
- Building document AI pipelines: OCR/extraction, parsing, normalization, chunking
- Embedding generation for semantic search and retrieval
- Vector similarity search and implementation with Vector Databases
- Integration of ML models with Vector DBs and MongoDB
- Proven experience writing scalable, maintainable, deployment-ready ML code
Qualifications
- CI/CD best practices and cloud deployment (Azure or AWS preferred)
- Production-level experience with document AI, embeddings, and semantic search
- Strong system design and code quality standards
- Observation, monitoring, and evaluation frameworks for production ML systems
- Cross-functional collaboration and clear technical communication
Skills
- Advanced Python development for ML/AI workloads
- Experience with the full ML lifecycle: model training, evaluation, fine-tuning, and labeling/tagging
- Generative AI systems design and LLM-based application development
- Prompt engineering for large language models
- Building document AI pipelines: OCR/extraction, parsing, normalization, chunking
- Embedding generation for semantic search and retrieval
- Vector similarity search and implementation with Vector Databases
- Integration of ML models with Vector DBs and MongoDB
- Proven experience writing scalable, maintainable, deployment-ready ML code
- CI/CD best practices and cloud deployment (Azure or AWS preferred)
- Production-level experience with document AI, embeddings, and semantic search
- Strong system design and code quality standards
- Observation, monitoring, and evaluation frameworks for production ML systems
- Cross-functional collaboration and clear technical communication
Benefits
- Medical Insurance
- Dental & Orthodontia Benefits
- Vision Benefits
- Health Savings Account (HSA)
- Health and Dependent Care Flexible Spending Accounts
- Voluntary Life Insurance, Long-Term & Short-Term Disability Insurance
- Hospital Indemnity Insurance
- 401(k) including match with pre and post-tax options
- Paid Sick Time Leave
- Legal and Identity Protection Plans
- Pre-tax Commuter Benefit
- 529 College Saver Plan