The Nuclear Company · Washington

Salary
$121,000–$165,000from the description
Posted
Jun 29, 2026
Location
Washington
Last confirmed open
Jul 21, 2026

What this job asks for AI summary

This role involves building and deploying machine learning and LLM-driven features into an internal software platform used to manage large-scale nuclear construction projects. Day-to-day work spans training and fine-tuning models, designing AI agent workflows, wiring up tool-use interfaces, and maintaining evaluation and monitoring systems in production. It suits an experienced ML engineer comfortable working across the full lifecycle — from data pipelines and model development through to production deployment — ideally with some background in regulated or safety-critical industries.

Senior level · 5+ years · Remote · Full-time

Must have (8)
PythonPyTorch or Hugging FaceLLMsRAGfine-tuningAI agentsdata pipelinesAWS, Azure or GCP
Nice to have (5)
Palantir FoundryPalantir AIPMCPMLflow, Sagemaker or Vertex AiCI/CD

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

Posted 2 times — it's one opening, so apply once.

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

Roughly 1,150 people nationally plausibly meet what this posting asks for (data scientists). range 330–1,700

Applicant volume Moderate — A normal amount of company. The rare requirements below are what will separate a shortlisted application from the rest.

What gives you an edge
RAG8%

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

What won't set you apart
Python88%data pipelines40%

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). This posting is about at that midpoint.

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)

No explicit work location or city is stated in the posting; the role appears to be remote or location-flexible based on the absence of any office requirement.

The degree requirement lists Bachelor's or Master's but explicitly accepts 'equivalent production experience' as a substitute, so no minimum degree is hard-gated.

AWS is listed as the preferred cloud ('AWS preferred') within the required section — it is a hard gate on cloud experience, with AWS as the named preference; Azure and GCP are listed as alternatives a hiring manager would accept.

Palantir Foundry and AIP are listed under Preferred Experience but the posting notes this is 'heavily weighted,' suggesting it is a strong differentiator rather than a strict gate; kept as preferred per section placement.

MCP (Model Context Protocol) appears in both the responsibilities narrative and the preferred section; it is treated as preferred since its only explicit qualification placement is under 'Preferred Experience.'

MLflow, SageMaker, and Vertex AI are listed together as MLOps options under Preferred Experience — emitted as a single preferred skill with alternatives.

The SOC classification is a close call between 15-2051 (Data Scientists, reflecting the ML modeling, fine-tuning, evals, and time-series work) and 15-1252 (Software Developers, reflecting the production shipping, agent engineering, and platform integration emphasis). 15-2051 is chosen as primary given the explicit ML/AI modeling focus, but confidence is Medium.

Ignored 1 non-technology phrase(s) as skills (responsibilities/concepts, not named tools): time-series analysis.

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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