Key job responsibilities
Set the technical direction for learning non-prehensile and contact-rich manipulation policies, from testing the latest advances in the field through demonstrated capability on hardware.
Oversee the development of reinforcement learning approaches that address the long tail of diverse, demanding manipulation conditions.
Own the path from simulation training to reliable, real-time execution on physical robots, making evidence based calls on where learned approaches should replace engineered ones.
Demonstrate new manipulation capabilities on real robots at scale, and turn one-off results into repeatable methods.
Establish the standards, evaluation practices, and data-informed improvement loops that the team builds on.
Mentor scientists and engineers, and raise the bar for applied science rigor and engineering quality.
Partner across control, perception, and hardware to integrate learned behaviors into working systems.
Represent Amazon in academia through publications and scientific presentations.
A day in the life
Amazon offers a full range of benefits that support you and eligible family members, including domestic partners. Benefits can vary by location, the number of regularly scheduled hours you work, length of employment, and job status such as seasonal or temporary employment. The benefits that generally apply to regular, full-time employees include:
1. Medical, Dental, and Vision Coverage
2. Maternity and Parental Leave Options
3. Paid Time Off (PTO)
4. 401(k) Plan
If you are not sure that every qualification on the list above describes you exactly, we'd still love to hear from you! At Amazon, we value people with unique backgrounds, experiences, and skillsets. If you’re passionate about this role and want to make an impact on a global scale, please apply
PhD or equivalent research experience
7+ years of applied research experience
3+ years of building machine learning models for business application experience
Experience programming in Java, C++, Python or related language
Track record of training reinforcement learning or imitation learning policies in simulation and successfully transferring them to physical systems
3+ years of building and deploying learning-based control on robotic systems
Experience leading technical projects and mentoring scientists or engineers
Experience with sim-to-real transfer at scale (domain randomization, system identification, etc)
Experience designing reward functions and training curricula for reinforcement learning on robotic systems
Experience with contact-rich or non-prehensile manipulation, including extrinsic dexterity and force/torque control
Publications in top robotics or machine learning venues (RSS, CoRL, ICRA, NeurIPS, ICML, etc.)
Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.
Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.
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 - 167,100.00 - 226,100.00 USD annually
