Robotics Simulation Scientist II — GPU RL & Sim-to-Real

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

Job summary

Amazon Robotics is seeking an Applied Scientist II for Robotics Simulation to design, build, and validate simulation environments and policy training pipelines that enable robots to learn manipulation and mobility skills in simulation and transfer them to real hardware.

You will work at the intersection of robotics simulation science and Physical AI, building GPU-accelerated RL environments, implementing imitation learning workflows, and reducing sim-to-real gaps across platforms and hardware.

Qualifications

• PhD or Master's degree required.
• 2+ years experience with physics simulation platforms for robot learning (MuJoCo, Isaac Sim/Lab, PyBullet, Drake, or equivalent).
• Experience training robot policies using RL or imitation learning and evaluating in simulation.
• Experience with articulated robot simulation and URDF/MJCF/USD formats.

Responsibilities

• Design and implement GPU-accelerated RL and imitation learning environments for manipulation and mobility tasks.
• Build and maintain policy training pipelines supporting diverse model architectures and evaluate policies in simulation.
• Characterize and reduce sim-to-real gaps through systematic validation against real robot data.
• Implement domain randomization strategies to improve policy robustness and transfer to real hardware.
• Develop sim-to-real transfer techniques including system identification and physics calibration.
• Create robot embodiment validation tests to ensure digital twins reflect real hardware.
• Contribute to design documents and technical reviews.

Skills

Physics simulation experience

RL/Imitation learning

Sim-to-real transfer

articulated robot simulation

URDF/MJCF/USD formats

GPU-accelerated simulation

Education

Master's or PhD in a relevant field

Tools

NVIDIA Isaac Lab/Sim

Omniverse

USD-based workflows

ROS2

Job description

Amazon Robotics is seeking an Applied Scientist II for Robotics Simulation to design, build, and validate simulation environments and policy training pipelines that enable robots to learn manipulation and mobility skills in simulation and transfer them to real hardware.

You will work at the intersection of robotics simulation science and Physical AI, building GPU-accelerated RL environments, implementing imitation learning workflows, and reducing sim-to-real gaps across platforms and hardware.