Machine Learning Engineer

Required Qualifications: U.S. citizenship and active T5/SSBI federally adjudicated clearance required.[8]+ years building applied ML/AI or data systems, with demonstrated delivery of LLM and RAG systems you personally built - not notebook demos. Hands-on Databricks. Document processing at scale: OCR, layout-aware parsing, chunking tradeoffs, poor-quality source handling. Local/self-hosted LLM serving - vLLM, TGI, Ollama, llama.cpp, or equivalent - including running open-weight models in an isolated or air-gapped environment without reliance on external API endpoints. Structured extraction and grounded generation with source attribution. LLM evaluation methodology - you can explain how you measured correctness and what the evaluation missed. Privacy-preserving synthetic data generation from CUI, PII, or comparably restricted source data, with an understanding of re-identification risk. Strong Python. Government or defense contracting experience.

Preferred Qualifications: RAG built inside a government or FedRAMP-authorized environment (Azure OpenAI in GCC High, AWS Gov Cloud, Bedrock within an authorized boundary).Direct experience with FedRAMP Moderate, NIST 800-171, CMMC L2, or CUI handling. Databricks Vector Search, Mosaic AI Agent Framework and Agent Evaluation, Asset Bundles, MLflow. Unity Catalog governance. H2O (h 2oGPTe, Driverless AI).We are an Equal Opportunity Employer committed to a diverse and inclusive workplace. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, age, gender identity, national origin, disability, or veteran status. We value diverse perspectives and actively seek to create an inclusive environment that celebrates the unique qualities of all employees.