mid machine learning Applied Scientist ic 4+ yrs Master's · Posted Mar 13, 2026
$171,600 – $222,200
USD per year

About this role

Amazon is hiring a mid-level Applied Scientist in the machine learning function based in Sunnyvale, CA. The posting calls out experience with Python, Java, Deep Learning, Data Structures and roughly 4+ years of relevant work. Listed education preference: a master's degree or equivalent. Compensation is listed at $171,600–$222,200 per year.

Role
Applied Scientist
Function
machine learning
Level
mid
Track
Individual contributor
Employment
Full-time
Location
Sunnyvale, CA
Experience
4+ years
Education
Master's degree
Department
Research Science
Posted
Mar 13, 2026
AI Summary
Develop and implement robot navigation systems for autonomous operation in complex indoor environments. Research classical and learning-based navigation methods, build evaluation frameworks, and conduct sim-to-real transfer experiments. Requires PhD or Master's with 4+ years CS/ML experience, programming proficiency, and publication/patent record.

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Job description

from Amazon careers

Join the Personal Robotics Group at Amazon, where you'll help pioneer intelligent robotic products that deliver meaningful customer experiences. As an Applied Scientist focused on Robot Navigation, you'll research and develop advanced navigation systems that enable robots to move reliably and safely through complex, dynamic environments. You'll work across a broad spectrum of navigation approaches—from classical methods to learning-based techniques and foundation models—to build robust solutions for autonomous robot navigation. In this role, you'll evaluate, adapt, and develop navigation methods that bridge the gap between state-of-the-art research and real-world deployment. You'll work closely with cross-functional teams to deliver integrated navigation capabilities that enable meaningful robot autonomy. Key job responsibilities Develop and implement robust navigation systems that enable reliable autonomous operation in complex, dynamic indoor environments with static and dynamic obstacles Build simulation-based and on-device evaluation frameworks with comprehensive benchmarks and metrics for systematic comparison of navigation methods Conduct sim-to-real transfer experiments, analyzing performance gaps and developing techniques to ensure reliable real-world navigation performance Collaborate with perception, manipulation, and other teams to ensure seamless integration of navigation capabilities into the full robot system Stay current with the latest advances in robot navigation, spatial reasoning, and related fields, and apply relevant findings…

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