Sr Applied Scientist, Amazon Supply Chain (Job ID 10488022)
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Amazon Development Center U.S., Inc. is recruiting a Senior Applied Scientist for AWS Applied AI Solutions (AAIS) in Seattle, Washington (Job ID 10488022). The role combines demand forecasting, inventory optimization, anomaly detection, machine learning, generative AI and agentic AI to develop customer-facing supply chain applications. Amazon lists a PhD or equivalent research experience and at least six years building machine learning models for business applications among its basic qualifications. The stated annual base salary range for Seattle is USD 167,100-226,100, excluding sign-on payments and restricted stock units (RSUs). The official job page displayed 'Apply now' when checked on October 16, 2026. The application link routes to the Amazon Jobs authentication flow; the post-login form was not tested and no application was submitted. The original job posting date is not established. October 16 is the verification date, not the original posting date.
Generic warehouse illustration only, not an Amazon facility. Photo: Willians Huerta / Pexels. Source: https://www.pexels.com/photo/industrial-warehouse-with-forklift-and-shelving-36398150/ - License: https://www.pexels.com/license/
This hiring signal brings mathematical optimization, predictive machine learning and agentic AI into the same supply chain product agenda, but hiring intent is not evidence of a deployed capability.
For supply chain executives and planning-system owners, the noteworthy question is whether AI-generated forecasts and recommendations can become feasible inventory and operational decisions, rather than simply more fluent explanations or automated interfaces. The value condition is evaluation against actual planning constraints, decision outcomes and production behavior, including offline tests and controlled experiments. The principal failure mode is automating a recommendation that looks plausible but violates lead times, network capacity, inventory economics or other operating constraints.
Amazon's stated role points to scientific investment in customer-facing supply chain applications; it does not establish product availability, performance gains or successful customer deployments.