Applied Scientist - Simulation and Large-Scale RL, Amazon Robotics - Vulcan Stow

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

Benefits offered by this job

Health insurance

401(k) matching

Paid time off

Parental leave

RSUs

Job summary

Amazon Robotics is seeking an Applied Scientist to advance reinforcement learning for manipulation across diverse, real-world environments. You will train policies in simulation at scale and transfer them to physical robots, contributing to a team that spans control, perception, and hardware.

The role emphasizes production-quality code and robust, scalable training pipelines. You will collaborate with scientists to publish research and demonstrate capabilities on real hardware, with a focus on

Qualifications

• PhD or Master’s with 4+ years in science, technology, engineering, or related field experience.
• Experience programming in Java, C++, Python or related language.
• Experience in patents or publications at top-tier peer‑reviewed conferences or journals.
• Experience training reinforcement learning or imitation learning policies for manipulation or robot control problems.
• Strong background in reinforcement learning, including reward design and training at scale in simulation.

Responsibilities

• Design and train reinforcement learning policies for non-prehensile and contact-rich manipulation, focused on diverse, demanding conditions.
• Build and scale simulation environments, training curricula, and reward formulations for policies transferable to real robots.
• Develop sim-to-real methods (domain randomization, system identification) and validate on hardware.
• Write production-quality code and own scalable training and evaluation pipelines.
• Evaluate policy behavior and failure modes, iterating between simulation and real-world testing to improve robustness.
• Collaborate with scientists and engineers across control, perception, and hardware to move ideas to demonstrated capability.
• Represent Amazon Robotics in academia through publications and presentations.

Skills

Java

C++

Python

Reinforcement learning

Imitation learning

Simulation

Policy training

Education

PhD, or Master's degree and 4+ years in STEM

Tools

Top-tier conferences/publications

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 unparalleled 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 advance reinforcement learning for manipulation. 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 training these policies in simulation at scale and transferring them to physical robots. 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 collect data, run experiments, and get new policies onto real hardware faster than almost anywhere in the field.

Key job responsibilities

• Design and train reinforcement learning policies for non-prehensile and contact-rich manipulation, focused on the long tail of diverse, demanding conditions.
• Build and scale simulation environments, training curricula, and reward formulations that produce policies which transfer to real robots.
• Develop sim-to-real methods (domain randomization, system identification, and related techniques) and validate them on physical hardware.
• Write production-quality code and own scalable, efficient training and evaluation pipelines.
• Evaluate policy behavior and failure modes, and iterate between simulation and real‑world testing to improve robustness.
• Partner with scientists and engineers across control, perception, and hardware to move ideas from prototype to demonstrated capability.
• 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

At Amazon, we value people with unique backgrounds, experiences, and skillsets.

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.

Basic Qualifications

• PhD, or Master's degree and 4+ years of science, technology, engineering or related field experience
• Experience programming in Java, C++, Python or related language
• Experience in patents or publications at top‑tier peer‑reviewed conferences or journals
• Experience training reinforcement learning or imitation learning policies for manipulation or robot control problems
• Strong background in reinforcement learning, including reward design and training at scale in simulation

Preferred Qualifications

• Experience in professional software development
• Experience with sim‑to‑real transfer (domain randomization, system identification, etc.), including transferring learned policies onto physical robots.
• Familiarity with learned dynamics or world models for manipulation

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