Explainable AI - Postdoctoral Researcher at LLNL
Livermore
$143,328from the description
Aug 11, 2026
Livermore
Sep 24, 2026
What this job asks for AI summary
A postdoctoral research position at Lawrence Livermore National Laboratory focused on explainable and interpretable AI — specifically recovering human-meaningful structure from deep model internals through sparse decompositions, concept discovery, mechanistic analysis, and causal intervention. The role also involves designing human-in-the-loop evaluation workflows and applying these methods to scientific machine learning and national security applications. It suits a recent PhD with a strong publication record in XAI or related areas.
Junior level · San Jose-Sunnyvale-Santa Clara, CA · Doctorate required · Temporary
“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
Roughly 30 people in the San Jose-Sunnyvale-Santa Clara, CA area plausibly meet what this posting asks for (data scientists). range 15–45
Applicant volume Moderate — A normal amount of company. The rare requirements below are what will separate a shortlisted application from the rest.
Rare in this occupation — lead with these, and say what you built with them.
Most people in this occupation already list these. Still required — just not what gets you shortlisted.
What the occupation pays Median $189,150 (middle half $152,859–$224,286). 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 Aug 15, 2026. It is a model, not a headcount.
Why we read it this way (8)
This is a fixed-term Postdoctoral appointment, renewable up to a maximum of three years; it is not a permanent staff position.
The CBSA used is San Jose-Sunnyvale-Santa Clara, CA (41940), which covers Livermore, CA — the laboratory's location. Some sources associate Livermore with the Oakland-Berkeley CBSA (41860); the San Jose CBSA is the closer match for the Tri-Valley area.
Seniority is set to Junior because this is an entry-level postdoctoral role explicitly open only to those who have recently been awarded a PhD — it is the first rung of a research career ladder, regardless of the intellectual depth of the work.
No security clearance is required at hire, though longer assignments trigger a background investigation process per the posting.
The NDAA Section 3112 restriction (limiting access for certain foreign nationals without US permanent residency or dual citizenship) is noted in the posting but cannot be represented in a structured field.
The posting lists 'deep learning' and 'explainable AI' as required competencies rather than specific named tools; they are included because the JD gates on demonstrated research experience in these areas. Generic methodology terms not tied to a named tool (e.g., mechanistic interpretability as a concept, causal intervention) are omitted per extraction rules.
Sparse autoencoders, GPU/HPC/cloud computing, and uncertainty quantification appear under 'Desired Qualifications' and are marked as preferred accordingly.
Posting is for a temporary engagement — the market benchmarks below price full-time roles, so read the comp comparison with that in mind.
Read the full posting
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