Senior Machine Learning Engineer -TS/SCI Clearance

Stott and May

Washington (District of Columbia)

On-site

USD 150,000 - 210,000

Full time

14 days+

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Job summary

Stott and May in Washington, DC, seeks a Machine Learning Engineer to design, deploy, and operate production LLM systems in secure, air-gapped environments. This role involves building end-to-end AI capabilities for mission-critical applications in national security contexts. You will own end-to-end systems, work across data pipelines to inference, and ship features into secure environments.

A U.S. Secret clearance is required; sponsorship is not provided; the team emphasizes high ownership and

Qualifications

  • Experience deploying ML systems into production.
  • Hands-on with LLMs, vector databases, or agentic workflows.
  • Comfortable owning systems end-to-end in a fast-moving environment.
  • Active U.S. Secret clearance (TS/SCI preferred).
  • No Sponsorship provided.

Responsibilities

  • Designing and deploying LLM systems (RAG, embeddings, vector search).
  • Building APIs and backend services for AI-powered applications.
  • Working across the full stack from data pipelines to inference.
  • Shipping systems into secure, sometimes air-gapped environments.

Skills

Production ML systems
LLMs
Vector databases
End-to-end ownership
Clearance (US Secret)
Sponsorship not provided

Tools

Vector databases

Job description

Machine Learning Engineers

Active U.S. Secret clearance required to be considered for this role.

Working on a high-impact opportunity with a venture-backed team building AI systems used in real-world national security environments.

This is not a research role.

You’ll be building and shipping production LLM systems that operate in secure, mission-critical settings.

What you’ll be doing
  • Designing and deploying LLM systems (RAG, embeddings, vector search)
  • Building APIs and backend services for AI-powered applications
  • Working across the full stack from data pipelines to inference
  • Shipping systems into secure, sometimes air-gapped environments
What they’re looking for
  • Experience deploying ML systems into production
  • Hands‑on with LLMs, vector databases, or agentic workflows
  • Comfortable owning systems end‑to‑end in a fast‑moving environment
  • Active U.S. Secret clearance (TS/SCI preferred)
  • No Sponsorship provided

Small, elite team. High ownership. Real impact.

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