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Salary
$167k – $226k per year
Location
In office (Seattle)
Seniority
Senior · 6+ years exp
Visa
H-1B filings in 12 months: 16,768 · for this role: 7,610 · green card filings: 56
Employment
Full-Time

Confirmed on the employer's own hiring board on Oct 18, 2026. First seen by Alion on Jun 2, 2026. Amazon scores A on the Alion truth index.

Overview
Company
Impact
Profile match
Amazon is an American technology and retail conglomerate founded by Jeff Bezos in 1994 as an online bookstore and headquartered in Seattle, Washington. It operates the world's largest online marketplace together with a global logistics network, physical grocery stores and a third-party seller platform that accounts for most units sold. Amazon Web Services, launched in 2006, is the leading public cloud provider and generates the majority of the group's operating profit, while advertising, Prime Video, Alexa devices and Kuiper satellite broadband round out the business.

Our team in Amazon Robotics builds robotic systems that perform contact-rich manipulation tasks 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 experienced Senior Applied Scientist to join our Motion Behaviors team. You will drive the development of learned controllers and manipulation behaviors, applying techniques like reinforcement learning and behavior cloning to robots operating in Amazon fulfillment centers. These problems remain unsolved at scale: our robots must improve continuously in environments where simulation alone is insufficient. You will make principled decisions about when learned approaches should replace engineered solutions, and how to select behaviors based on estimated risk. You will collaborate across disciplines and leverage rich operational data to continuously improve system performance.

Key job responsibilities

  • Drive the development of learned controllers and manipulation behaviors, from research prototyping through deployment on production robots.
  • Research, design, and implement motion planning, control, and decision-making algorithms that improve the performance of deployed systems.
  • Design and deploy learning pipelines that take policies from simulation training to reliable, real-time execution on physical robots.
  • Develop models that predict manipulation outcomes and inform behavior selection under uncertainty.
  • Own the development of scalable, real-time implementations - writing production-quality code and setting engineering standards for the team.
  • Leverage operational data from deployed systems to systematically identify failure modes and drive policy improvements.
  • Mentor junior scientists and engineers, raising the bar for applied science rigor and engineering quality.
  • Represent Amazon in academia through publications and scientific presentations. A day in the life Amazon offers a full range of benefits for 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 6+ years of applied research experience

- Experience programming in Java, C++, Python or related language

- 4+ years of robotics work cells and control systems experience

- 3+ years of building and deploying machine learning models for robotics applications

- Track record of training reinforcement learning or imitation learning policies in simulation and successfully transferring them to physical robotic systems

Preferred qualifications

- Experience with sim-to-real transfer at scale (domain randomization, system identification, etc.)

- Experience deploying learned policies in production environments with uptime and reliability requirements

- Experience designing reward functions and training curricula for reinforcement learning on robotic systems

- 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

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