Applied Scientist - On-Robot Learning, Amazon Robotics - Vulcan Stow

Amazon Science; Seattle (WA); On-site; USD 143,000 - 193,000; Full time

Job summary

Amazon Science in Seattle seeks an Applied Scientist to bring learned manipulation policies to life on real robots. You will focus on making learned, contact-rich, non-prehensile behaviors work reliably on hardware, closing the loop between policy and real contact, sensing, and dynamics.

You will join a small team advancing manipulation capabilities across products, with opportunities to publish and collaborate with control, perception, and hardware experts.

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.

Responsibilities

• Deploy and evaluate learned manipulation policies on physical robots, focused on the long tail of diverse, demanding conditions.
• Diagnose the gap between simulated and real behavior, and drive the changes in policies, rewards, sensing, or control that close it.
• Develop tactile, actuation, 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.

Skills

Java

C++

Python

Reinforcement learning

Learning-based manipulation

Contact-rich control

Force/torque control

Patents or publications

Education

PhD

Masters + 4+ years experience

Job description

Description
Our organization in Amazon Robotics builds robots that perform contact-rich manipulation safely and reliably in complex, unstructured environments, at Amazon scale. Our scientists and engineers push the boundaries of robotic manipulation to handle enormous object diversity, bringing deep expertise across planning, control, perception, and machine learning. We learn from real-world data at a scale that few teams in robotics can access.

Description
Our organization in Amazon Robotics builds robots that perform contact-rich manipulation safely and reliably in complex, unstructured environments, at Amazon scale. Our scientists and engineers push the boundaries of robotic manipulation to handle enormous object diversity, bringing deep expertise across planning, control, perception, and machine learning. We learn from real-world data at a scale that few teams in robotics can access.

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, demanding conditions.
• Diagnose the gap between simulated and real behavior, and drive the changes in policies, rewards, sensing, or control that close it.
• Develop tactile, actuation, 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.

A day in the life

Amazon offers a full range of benefits that assist 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:

• Medical, Dental, and Vision Coverage
• Maternity and Parental Leave Options
• Paid Time Off (PTO)
• 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!

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.)

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 - 142,800.00 - 193,200.00 USD annually