ML Engineer

We are looking for ML Engineer for our client in Woodland Hills, CA.

Job Title: ML Engineer

Job Location: Woodland Hills, CA

Job Type: Contract

Job Overview:

Pay Range: $56.00hr - $61.00hr

Requirement/Must Have:

• 8+ years of Python development experience.
• 5+ years of Machine Learning model development and training.
• 3+ years of Generative AI / LLM solution development.
• 3+ years of Vector Database, Embeddings, and RAG implementation.
• 2+ years of A2A (Agent-to-Agent) and MCP (Model Context Protocol) implementation experience.
• 2+ years of AI Agent and Multi-Agent System development experience.
• Expert-level proficiency in Python.
• Strong experience in 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 working with Vector Databases and/or MongoDB.

Responsibilities:

• Design and develop scalable ML and Generative AI solutions.
• 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.

Nice to Have:

• LangChain / LangGraph.
• LlamaIndex.
• OpenAI / Azure OpenAI.
• A2A Agent Frameworks.
• Vector DBs (Pinecone, Chroma, Weaviate, Milvus, FAISS).
• Hugging Face.
• MLflow.
• FastAPI.
• Docker & Kubernetes.

Skills:

• Python (Expert Level).
• Machine Learning Model Training & Fine-Tuning.
• Generative AI.
• LLMs.
• Prompt Engineering.
• A2A (Agent-to-Agent Communication).
• MCP (Model Context Protocol).
• Vector Databases.
• Embeddings.
• RAG.
• MongoDB.
• Document Extraction.
• Parsing & Chunking.
• AI Agent Development.
• Agent Orchestration Frameworks.

Qualification And Education:

• Expert-level proficiency in Python.
• Strong experience in 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 working with Vector Databases and/or MongoDB.

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• Medical, Dental, and Vision Insurance
• 401(k) Retirement Plan
• Health Savings Account (HSA)
• Disability Insurance (Short-Term and Long-Term)
• Life and AD&D Insurance
• Paid Sick Leave (where required by applicable state or local law)
• Supplemental Insurance Plans
• Identity Theft Protection
• Pet Insurance
• Employee Wellness Programs
• Employee Assistance Program (EAP)
• Career Growth and Professional Development Opportunities