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

Amazon; Sunnyvale (CA); On-site; USD 172,000 - 222,000; Full time

Job summary

Amazon Robotics invites applications for an Applied Scientist to design, build, and validate GPU-accelerated 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 modern Physical AI, building RL environments, imitation workflows, and sim-to-real validation.

Qualifications

• PhD or Master's degree.
• 2+ years of experience with physics simulation platforms for robot learning (MuJoCo, Isaac Sim/Lab, PyBullet, Drake, or equivalent).
• Demonstrated experience training robot policies using reinforcement learning or imitation learning.
• Experience with articulated robot simulation, including URDF/MJCF/USD formats and rigid/soft body dynamics.
• Familiarity with sim-to-real transfer concepts (domain randomization, system identification, or physics calibration).

Responsibilities

• Design and implement GPU-accelerated reinforcement learning and imitation learning environments in NVIDIA Isaac Lab for manipulation and mobility tasks.
• Build and maintain policy training pipelines supporting diverse model architectures and evaluate trained policies in simulation.
• Characterize and reduce sim-to-real gaps through systematic validation against real-world data and implement improvements.
• Implement domain randomization strategies to improve policy robustness and transfer to real hardware.
• Develop sim-to-real transfer techniques including system identification and physics parameter calibration.
• Create robot embodiment validation tests to ensure digital twins match real hardware.
• Build data pipelines for recording, replaying, and augmenting demonstration data to scale training data volume.
• Contribute to end-effector modeling and contact dynamics tuning for realistic interactions.
• Author design documents for new simulation science capabilities and participate in technical reviews.
• Collaborate with partner science teams to align simulation with training requirements.

Skills

Physics-based learning

Reinforcement learning

Imitation learning

URDF/MJCF/USD formats

GPU-accelerated simulation

Education

PhD or Master's degree

Tools

MuJoCo

Isaac Sim/Lab

PyBullet

Drake

NVIDIA Isaac Lab/Sim

Omniverse

Job description

Amazon Robotics invites applications for an Applied Scientist to design, build, and validate GPU-accelerated 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 modern Physical AI, building RL environments, imitation workflows, and sim-to-real validation.