principal machine learning Applied Scientist tech_leadership · Posted Jun 3, 2025
$228,700 – $309,400
USD per year

About this role

Amazon is hiring a principal-level Applied Scientist in the machine learning function based in Bellevue, WA. The posting calls out experience with Python, SQL, Spark, Deep Learning. Compensation is listed at $228,700–$309,400 per year.

Role
Applied Scientist
Function
machine learning
Level
principal
Track
Tech leadership
Employment
Full-time
Location
Bellevue, WA
Department
Applied Science
Posted
Jun 3, 2025
AI Summary
Principal Applied Scientist developing foundation models for Amazon's Last Mile delivery network. Design multimodal deep learning architectures, solve large-scale training and inference problems, mentor scientists, and guide technical initiatives from research through production deployment.

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Job description

from Amazon careers

Join the next science and engineering revolution at Amazon's Delivery Foundation Model team, where you'll work alongside world-class scientists and engineers to pioneer the next frontier of logistics through advanced AI and foundation models. We are seeking an exceptional Principal Applied Scientist to help develop innovative foundation models that enable delivery of billions of packages worldwide. In this role, you'll combine highly technical work with scientific leadership, ensuring the team delivers robust solutions for dynamic real-world environments. Your team will leverage Amazon's vast data and computational resources to tackle ambitious problems across a diverse set of Amazon delivery use cases. Key job responsibilities - Design and implement novel deep learning architectures combining a multitude of modalities, including image, video, and geospatial data. - Solve computational problems to train foundation models on vast amounts of Amazon data and infer at Amazon scale, taking advantage of latest developments in hardware and deep learning libraries. - As a foundation model developer, collaborate with multiple science and engineering teams to help build adaptations that power use cases across Amazon Last Mile deliveries, improving experience and safety of a delivery driver, an Amazon customer, and improving efficiency of Amazon delivery network. - Guide technical direction…

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