Sr Applied Scientist, Applied AI Solutions
Amazon · Seattle, WA
$167,100–$226,100from the description
Jul 9, 2026
Seattle, WA
Jul 21, 2026
What this job asks for AI summary
A senior research and engineering role focused on building multi-agent and generative AI systems within an AWS business-applications team. Day-to-day work spans the full ML lifecycle — from researching novel approaches and modeling large datasets to deploying and optimizing models in production alongside software engineers. Suited to someone with deep experience in large language models, agentic architectures, and applied ML at scale.
Senior level · 6+ years · Seattle-Tacoma-Bellevue, WA · Master's required · Full-time
“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 270 people in the Seattle-Tacoma-Bellevue, WA area plausibly meet what this posting asks for (data scientists). range 210–360
Applicant volume Moderate — A normal amount of company. The rare requirements below are what will separate a shortlisted application from the rest.
Most people in this occupation already list these. Still required — just not what gets you shortlisted.
What the occupation pays Median $168,363 (middle half $111,131–$214,996). 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 (8)
The Basic Qualifications state a PhD, OR a Master's degree with 6+ years of applied research experience — the degree requirement is set to Masters (the minimum formal degree that satisfies the gate); a PhD alone (with fewer years) also qualifies.
The '3+ years of building machine learning models' requirement is a separate gate from the '6+ years of applied research' tied to the Master's path; the overall years minimum is set to 6 to reflect the higher bar that applies to the most common (Master's) path.
'Experience using managed ML/AI solutions' is listed as a Basic Qualification but names no specific platform; it is captured as a required skill with the phrasing used in the JD since no canonical tool name is given.
LLMs and agentic systems are called out prominently in the role description and key responsibilities as the core technical focus, but they do not appear under the formal Basic Qualifications section — they are treated as required given the explicit framing ('You will be responsible for building the state-of-art multi-agent system') rather than merely preferred.
Reinforcement learning and fine-tuning appear in the role narrative ('using a handful of methods including fine-tuning, reinforcement learning') as context for the work, not under a formal requirements heading — listed as preferred.
The alternative occupation code 15-1252 (Software Developers) is noted because the role involves building and deploying production ML systems end-to-end, but the primary day-to-day work is applied research and modeling, making 15-2051 the better fit.
Compensation is quoted as a base salary range; the posting also mentions sign-on payments and RSUs as additional components.
Ignored 1 non-technology phrase(s) as skills (responsibilities/concepts, not named tools): managed ML/AI solutions.
Read the full posting
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