principal machine learning Applied Scientist hybrid · Posted May 6, 2026
$202,200 – $273,600
USD per year

About this role

Amazon is hiring a principal-level Applied Scientist in the machine learning function based in New York City, NY. The posting calls out experience with Python, Java, LLMs, RAG. Compensation is listed at $202,200–$273,600 per year.

Role
Applied Scientist
Function
machine learning
Level
principal
Track
hybrid
Employment
Full-time
Location
New York City, NY
Department
Applied Science
Posted
May 6, 2026

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Job description

from Amazon careers

The Sponsored Products and Brands team at Amazon Ads is re-imagining the advertising landscape through industry leading generative AI technologies, revolutionizing how millions of customers discover products and engage with brands across Amazon.com and beyond. We are at the forefront of re-inventing advertising experiences, bridging human creativity with artificial intelligence to transform every aspect of the advertising lifecycle from ad creation and optimization to performance analysis and customer insights. We are a passionate group of innovators dedicated to developing responsible and intelligent AI technologies that balance the needs of advertisers, enhance the shopping experience, and strengthen the marketplace. If you're energized by solving complex challenges and pushing the boundaries of what's possible with AI, join us in shaping the future of advertising. As the Applied Science Manager for the Continuous Model Evaluation and Learning workstream, you will own the quality backbone for this agentic brand-intelligence system. You will lead a mix of applied scientists and engineers who define what "good" looks like for each brand skill, instrument the system to measure it, diagnose why skills underperform, and close the loop by generating, validating, and deploying improvements. You will deliver the evaluation and remediation framework that attains accuracy targets, enables forward…

This is an excerpt. Read the full job description on Amazon careers →
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