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Applied Scientist II, Physics Simulation, Amazon Industrial Robotics

Amazon

Applied Scientist II, Physics Simulation, Amazon Industrial Robotics

Amazon

N.reading, MA, USA

·

On-site

·

Full-time

·

3w ago

Compensation

$142,800 - $193,200

Benefits & Perks

Healthcare

401(k)

Equity

Paid Time Off

Parental Leave

Mental Health

Healthcare

401k

Equity

Parental Leave

Mental Health

Required Skills

C++

Python

Physics Simulation

Numerical Methods

Amazon Industrial Robotics is seeking exceptional talent to help develop the next generation of advanced robotics systems that will transform automation at Amazon's scale. We're building revolutionary robotic systems that combine cutting-edge AI, sophisticated control systems, and advanced mechanical design to create adaptable automation solutions capable of working safely alongside humans in dynamic environments. This is a unique opportunity to shape the future of robotics and automation at an unprecedented scale, working with world-class teams pushing the boundaries of what's possible in robotic dexterous manipulation, locomotion, and human-robot interaction.

We are seeking a talented Applied Scientist to join our advanced robotics team, focusing on developing and applying cutting-edge simulation methodologies for advanced robotics systems. This role centers on research and development of physics-based simulation techniques, sim-to-real transfer methods, and machine learning approaches that enable rapid development, testing, and validation of robotic systems operating in complex, real-world environments.

  • Key job responsibilities

  • Advance physics-based simulation fidelity for contact-rich manipulation and locomotion

  • Design and build high-performance simulation tools integrated into a production robotics stack

  • Translate research ideas into robust, scalable software pipelines

  • Develop methods to quantify and reduce simulation-to-reality gaps across design, safety, and control

  • Architect scalable simulation solutions for rigid and deformable body dynamics

  • Build simulation pipelines optimized for large-scale reinforcement and policy learning

  • Establish frameworks for continuous simulation improvement using real-world deployment data

  • Collaborate with engineering, science, and safety teams on simulation requirements and validation

About the team
Our team is building a comprehensive simulation platform for advanced robotics development, combining locomotion and manipulation capabilities. We operate at the cutting edge of physics simulation, reinforcement learning, and sim-to-real transfer, collaborating with world-class robotics engineers, applied scientists, and mechanical designers in a fast-paced, innovation-driven environment.

This role uniquely combines fundamental research with real-world deployment. You will pursue core research questions in physics-based simulation while seeing your work translated into production systems, validated on real hardware, and informed by deployment data. Working alongside Simulation Software Engineers, you will help transform research ideas into scalable, production-grade simulation capabilities that directly impact how robots are designed, trained, and deployed.

Basic Qualifications

  • Currently has, or is in the process of obtaining, a PhD in computer science, computer engineering, or related field
  • 2+ years of science, technology, engineering or related field experience
  • Deep expertise in physics-based simulation, including rigid and deformable dynamics, contact mechanics, computational geometry, and numerical methods
  • Experience designing and optimizing physics-based simulation systems for high-performance and large-scale computing environments
  • Strong programming skills in C++ and Python, with an emphasis on maintainable, performance-critical code
  • Working knowledge of modern physics engines such as Mu JoCo, Isaac Lab, Drake, and Newton

Preferred Qualifications

  • Experience with reinforcement learning and policy training in simulation
  • Familiarity with differentiable physics, learned simulation models, or neural physics engines
  • Background in contact-rich manipulation or legged locomotion simulation
  • Experience with robotics model formats and pipelines (e.g., URDF, SDF, USD)
  • Expertise in GPU-accelerated computing and algorithms
  • Experience deploying simulation-trained policies on real robotic systems
  • Demonstrated research leadership, from project conception through publication and deployment

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, MA, N.Reading - 142,800.00 - 193,200.00 USD annually

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About Amazon

Amazon

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Amazon.com, Inc. is an American multinational technology company engaged in e-commerce, cloud computing, online advertising, digital streaming, and artificial intelligence.

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Good pay and compensation

Strong benefits package

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Poor management and leadership

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total / year

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$154,672

$209,264

Interview Experience

10 interviews

Difficulty

3.7

/ 5

Duration

21-35 weeks

Offer Rate

20%

Experience

Positive 10%

Neutral 10%

Negative 80%

Interview Process

1

Application Review

2

Recruiter Screen

3

Online Assessment

4

Technical Phone Screen

5

Onsite/Virtual Loop

6

Team Matching

7

Offer

Common Questions

Coding/Algorithm

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Behavioral/STAR

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Technical Knowledge