Applied Scientist, SPX AI Lab at Amazon
Seattle, WA
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Jul 16, 2026
Seattle, WA
Jul 21, 2026
What this job asks for AI summary
This role focuses on building and advancing a multi-agent AI system designed to assist Amazon's third-party sellers. Day-to-day work involves designing, training, and deploying machine learning and generative AI models in a production environment, as well as establishing automated pipelines for data analysis, model validation, and benchmarking. It suits scientists with hands-on ML development experience who want to ship real products at large scale rather than conduct purely exploratory research.
Senior level · 4+ years · National · 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
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 (8)
The role title is 'Applied Scientist' with no explicit seniority level in the title; advertised seniority is Unspecified. However, the combination of a PhD/Master's + 4 years requirement, 3+ years of ML model-building, and end-to-end ownership of production systems supports a Senior classification.
Degree requirement: the JD states 'PhD, or Master's degree and 4+ years' — a Master's is the minimum hard-required degree path (a PhD alone with no years qualifier is the other path). Classified as Masters.
The overall years minimum of 4 reflects the Master's + 4 years path; the PhD path has no stated minimum years.
Location is not specified in the posting. Amazon roles of this type are typically US-based; no CBSA or state could be determined.
The Basic Qualifications list 'algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high-performance computing' as an 'any of the following' gate — meaning at least one is required. 'Algorithms and data structures' is listed as the representative required skill; the others are genuine alternatives within that single gate.
Generative AI, LLMs, and prompt engineering appear only under Preferred Qualifications and are marked accordingly.
The alternative occupation 15-1252 (Software Developers) is noted because the role involves designing, developing, and deploying production-grade models and systems, but the primary day-to-day work is ML/AI science, making 15-2051 the better fit.
Ignored 1 non-technology phrase(s) as skills (responsibilities/concepts, not named tools): algorithms and data structures.
Read the full posting
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