Staff Applied ML Engineer, Federal/National Security

Role overview Build and deploy applied AI systems for federal and national-security missions, taking modern language models from experimentation into dependable operational software. The work spans model adaptation, retrieval, agents, evaluation, and inference, while staying close to users and the workflows the systems need to support. Solutions should be adaptable across cloud, on-premises, and edge settings, and reusable across deployments.

Responsibilities - Build production applications powered by language models, including agents and multi-step workflows. - Develop evaluation, fine-tuning, adaptation, and experimentation pipelines. - Choose among prompting, retrieval-augmented generation, fine-tuning, and specialized models based on the task. - Measure model and agent quality, reliability, tool use, and task completion with rigorous evaluations. - Create retrieval and context systems for structured and unstructured mission data, and optimize models for production inference. - Work with deployment engineers and customers to translate operational needs into AI capabilities, then turn deployment-specific solutions into reusable platform features.

Requirements - Significant experience building and deploying machine-learning or AI systems in production. - Hands-on experience with modern language and foundation models, plus deep expertise in several areas such as fine-tuning, evaluation, retrieval, agents, inference, embeddings, synthetic data, or reliability safeguards. - Ability to move between model experimentation and production engineering, and to work independently on ambiguous problems. - Interest in working close to users and assessing how AI performs in real operational workflows. - U.S. citizenship and an active Secret or Top Secret clearance are required.

Nice to have Experience across multiple AI disciplines is valuable, particularly the ability to assess when different approaches are appropriate and make their performance measurable.

Benefits and work setup Washington, DC or Northern Virginia is preferred. The role may involve regular customer-facing work, onsite meetings, secure-facility work, or travel depending on program needs. The listed salary range is $180,000–$240,000, plus bonus and equity. Benefits may vary by organization and include employer-paid medical, dental, and vision coverage, 14 weeks of paid parental leave, manager-approved unlimited paid time off, professional development, and optional retirement, flexible-spending, and equity programs.