Applied Scientist - Simulation and Large-Scale RL, Amazon Robotics - Vulcan Stow
Company websiteamazon.com (Amazon, opens in new tab)
Base salary $142,800 to $193,200
Employer-published annual base salary, USD. Advertised base range in Seattle, WA
You apply on the employer's own site. Six Figure Work does not handle applications.
- LocationSeattle, WA
- WorkplaceWorkplace not stated
- Status at last checkSource accepting applications when checked
- Last checked (1 h ago) · observed since
About this job
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:
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!
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
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
Source: Amazon · View original posting (opens in new tab)
Pay in context
This role's base floor ($142,800) is above 28% of the 329 Data & ML roles in Washington listed on this site; 69 others list the same floor. Their median floor is $143,700; the middle half runs from $136,000 to $168,000.
Only jobs on this site count, and each one publishes a base salary of $100,000 or more, so this compares six-figure jobs with each other, not with the whole market. Computed Nov 7, 2026.
This listingApplied Scientist - Simulation and Large-Scale RL, Amazon Robotics - Vulcan Stow$142,800 to $193,200
Customer Insights Lead, Global Logistics Domestic First Mile$142,800 to $193,200
Senior Product Marketing Manager, GTM Lead, Fashion & Fitness Marketing$142,800 to $193,200
Applied Scientist, BRP Payment Risk ML, BRP Payment Risk ML$142,800 to $193,200
Applied Scientist, Denied Party Screening (DPS), AWS Compliance & Security Assurance$142,800 to $193,200
Simulation & Modeling Applied Scientist, Prime Air Flight Sciences High Fidelity Methods$142,800 to $193,200
Applied Scientist, AWS Payments and Fraud Prevention$142,800 to $193,200
Chart as a table
| Role | Published base |
|---|---|
| Applied Scientist - Simulation and Large-Scale RL, Amazon Robotics - Vulcan Stow (this listing) | $142,800 - $193,200 |
| Customer Insights Lead, Global Logistics Domestic First Mile | $142,800 - $193,200 |
| Senior Product Marketing Manager, GTM Lead, Fashion & Fitness Marketing | $142,800 - $193,200 |
| Applied Scientist, BRP Payment Risk ML, BRP Payment Risk ML | $142,800 - $193,200 |
| Applied Scientist, Denied Party Screening (DPS), AWS Compliance & Security Assurance | $142,800 - $193,200 |
| Simulation & Modeling Applied Scientist, Prime Air Flight Sciences High Fidelity Methods | $142,800 - $193,200 |
| Applied Scientist, AWS Payments and Fraud Prevention | $142,800 - $193,200 |
Observed changes
- First observed on the employer's board
- Began meeting the published-salary criteria
- Observed since
- Employer-stated posting date
- 2026-08-11
Where this pay comes from
Location as the employer wrote it: US, WA, Seattle
USA, WA, Seattle - 142,800.00 - 193,200.00 USD annually
- Method
- Employer text, read with fixed rules and re-verified
- Checked
- Rule set
- us-base-v2
The pay passage appears in the employer's own job text. Fixed, deterministic rules located it, and the passage below was checked against the stored copy of the posting.
What we verified
- The pay figures come from the employer's own listing, quoted exactly above.
- The pay is an annual base salary in US dollars with a minimum of at least $100,000.
- The role was publicly listed on the employer's job board when last checked.
We do not verify what the employer will actually offer, whether the employer is still recruiting for the role, or anything beyond what the employer published. Full methodology.
