Expression · Washington, DC

Salary
$130,000–$170,000
Posted
Jul 7, 2026
Location
Washington, DC
Last confirmed open
Jul 21, 2026

What this job asks for AI summary

This role centers on building and deploying machine learning systems designed to run on edge hardware with limited compute and bandwidth — from embedded processors up to workstation-class machines. Day-to-day work spans optimizing and evaluating open-weight foundation models, building inference pipelines and RAG workflows, designing AI orchestration across distributed edge devices, and integrating those capabilities into production software. It suits an applied ML engineer with hands-on LLM deployment experience and a background in edge or resource-constrained environments; eligibility for a U.S. security clearance is required.

Senior level · 5+ years · Remote · Bachelor's required · Secret clearance · Full-time

Must have (10)
PythonPyTorchLLMsLangGraph, LangChain, Crewai or Semantic KernelRAGvector databasesedge AImodel quantizationDockerAI evaluation frameworks
Nice to have (5)
sensor analyticstime-series dataRF analyticsmultimodal AIdistributed edge computing

“or” means any one of them counts — you don't need all of them.

We read this from the posting text with AI. Skim the description below before ruling yourself out.

How this req sits in the market our data

What gives you an edge
LangGraph6%vector databases6%RAG8%

Rare in this occupation — lead with these, and say what you built with them.

What won't set you apart
Python88%Docker53%

Most people in this occupation already list these. Still required — just not what gets you shortlisted.

What the occupation pays Median $122,874 (middle half $87,544–$162,374).

Estimated from BLS employment for this occupation and area, per-skill prevalence across our listing corpus, and published wage benchmarks — as of Jul 28, 2026. It is a model, not a headcount.

Why we read it this way (9)

The title carries no seniority level; 'Unspecified' is set for advertised seniority. The 5-8+ years requirement and production-deployment scope support a Senior classification.

Clearance is stated as 'eligible to obtain Secret or Top Secret' — this is a gate on US citizenship and clearance eligibility, not on holding an active clearance. The lowest stated level (Secret) is used; candidates need not already hold a clearance but must be eligible.

The role is listed as 'Hybrid or Remote' — remote=true is set, though some travel and potential on-site work is implied.

The orchestration framework requirement names LangGraph, LangChain, CrewAI, and Semantic Kernel as interchangeable options; LangGraph is used as the primary with the others in alternatives.

Model optimization (quantization, pruning, distillation) is listed as a single required capability; 'model quantization' is used as the canonical name representing the broader compression/acceleration requirement.

An advanced degree is explicitly noted as preferred, not required; the degree requirement is set to Bachelors (the stated minimum).

No compensation figures are provided in the posting.

Requires a Secret clearance — the cleared population is a small fraction of this occupation, so the real candidate pool is materially smaller than the estimate below, which does not model clearance.

This posting reads as a fully-remote role, so it was scored against the national candidate pool rather than a single metro.

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