Staff Applied ML Engineer, Federal/National Security
Core
Build and deploy production AI systems, LLM-powered applications, and agentic workflows for federal and national security missions.
Role type
Staff Applied ML Engineer (Production AI & Agentic Systems)
Builds
Production LLM applications, AI agents, agentic workflows, and retrieval systems for mission environments
Domain
National Security / Federal Government / Applied AI
Deliverable
production ML models | product features
Required skills
LLM fine-tuning and adaptation, model evaluation, RAG and retrieval systems, agentic systems and tool use, model serving and inference, embeddings and knowledge retrieval, synthetic data generation, AI guardrails and reliability engineering, production engineering for ambiguous problems
Preferred skills
Experience moving between ML experimentation and production engineering, ability to operate independently, customer-facing experience
Technologies
LLMs, foundation models, agentic frameworks, RAG architectures, model evaluation frameworks, inference optimization tools
Responsibilities
Build production LLM-powered applications and agentic workflows; Develop and own model evaluation, fine-tuning, and experimentation pipelines; Determine optimal approaches (prompting, RAG, fine-tuning) for mission problems; Build rigorous eval systems for model and agent quality; Develop retrieval systems across structured and unstructured data; Optimize models and inference for production; Deploy and improve models based on real-world feedback; Partner with Forward Deployed Engineers and customers to translate requirements into AI capabilities
Seniority
Staff, hands-on IC with strategic impact