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.

==

Benefits

Our Benefits Include

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

Disclaimer: Benefits eligibility, accrual rates, and usage limits may vary based on employment status, length of service, and work location. Paid Sick Leave is provided in strict accordance with applicable state and municipal mandates. Cynet Systems Inc. reserves the right to modify, amend, or terminate any benefit plans at any time in accordance with applicable laws.

About Cynet Systems

Founded in 2010 and headquartered in the Washington, DC metro area, Cynet Systems Inc. is a leading technology staffing and workforce solutions company serving Fortune 500 companies, government agencies, and enterprise organizations across the United States and Canada. We deliver agile, scalable talent solutions across IT, engineering, life sciences, clinical, and professional staffing, powered by a high-performing recruitment engine operating across North America and Asia.

As a nationally and locally certified Minority Business Enterprise (MBE), Cynet Systems is committed to helping organizations build high-performing teams while empowering professionals to grow rewarding careers. Our organization is certified to ISO 9001, ISO 14001, ISO 27001, and SOC 2 Type II standards, reflecting our commitment to quality, security, operational excellence, and customer success.