Full Job Description
We are seeking an Applied Scientist to bring learned manipulation policies to life on real robots. We are creating robots that learn how to push, flip, rearrange, and dexterously insert items with unparalleled robustness, speed, and reliability. Our goal is to deploy robots that will work across Amazon's global network and can handle the full diversity of items that Amazon sells. You will focus on making learned, contact-rich, non-prehensile behaviors work reliably on physical hardware, closing the loop between what a policy does in simulation and how it behaves against real contact, sensing, and dynamics. You will join a small team whose mission reaches beyond any single product: to invent and apply manipulation capabilities that generalize to many future robotics applications. The robots our organization already deploys at scale give you a rare proving ground to test new policies and behaviors on real hardware faster than almost anywhere in the field.
Key job responsibilities
- Deploy and evaluate learned manipulation policies on physical robots, focused on the long tail of diverse, complex conditions.
- Diagnose the gap between simulated and real behavior, and drive the changes in policies, rewards, sensing, or control that close it.
- Develop tactile, force, and contact-aware methods that make non-prehensile manipulation fast, assured, and robust.
- Write production-quality code and own scalable, real-time implementations that run on robots.
- Build the data collection, logging, and evaluation loops that turn real-world experience into policy improvements.
- Partner with scientists and engineers across control, perception, and hardware to move ideas from prototype to demonstrated capability on hardware.
- Represent Amazon Robotics in academia through publications and scientific presentations.
BASIC QUALIFICATIONS
- 3+ years of building models for business application experience
- PhD, or Master's degree and 4+ years of science, technology, engineering or related field experience
- Experience in patents or publications at top-tier peer-reviewed conferences or journals
- Experience programming in Java, C++, Python or related language
- Hands-on experience deploying and evaluating learning-based control or manipulation on physical robots
- Strong background in one or more of: reinforcement learning, learning-based manipulation, contact-rich control, or force/torque control
PREFERRED QUALIFICATIONS
- Experience in professional software development
- Experience with contact-rich control or manipulation policies, tactile sensing, or compliant control on physical systems
- Experience deploying and supporting complex robotic systems at scale
- Publications in top robotics or machine learning venues (RSS, CoRL, ICRA, IROS, NeurIPS, ICML, etc.)
The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave. Learn more about our benefits at https://amazon.jobs/en/benefits.
USA, WA, Seattle - 142,800.00 - 193,200.00 USD annually
