Senior Research Engineer, Simulation

NVIDIA’s Generalist Embodied Agent Research (GEAR) group is leading Project GR00T, a moonshot initiative to build foundation models and full-stack technology for humanoid robots. Join an amazing, collaborative research team that consistently produces influential works on multimodal foundation models, large-scale robot learning, embodied AI, and physical simulation. Past projects include Eureka, VIMA, Voyager, MineDojo, MimicPlay, and Prismer. Your contributions will have a significant impact on our research projects and product roadmaps.

Responsibilities

• Develop and maintain simulation environments built on frameworks like MuJoCo and Isaac Lab to support robotics research.
• Implement and test control algorithms and XR teleoperation interfaces for simulated robots.
• Build procedural generation pipelines for diverse environments, object layouts, and robot motions.
• Optimize GPU-based physics simulator performance for large-scale training workloads.
• Import, configure, and validate robot assets in USD format, ensuring successful sim2real transfer.
• Implement Sim2Real pipelines and deploy learned models to physical robots.

Requirements

• Bachelor’s degree or above in Computer Science, Robotics, Engineering, or a related field.
• 10+ years of full-time industry experience in robotics and/or physics simulation.
• Proven experience with one or more physics simulators such as MuJoCo, Isaac Sim, PyBullet, Drake, or Gazebo.
• Deep knowledge of state-of-the-art simulation techniques, including accurate contact dynamics for manipulation and locomotion, and photorealistic rendering for perception.
• Expertise in generating simulation assets, task definitions, and building Gym-style APIs to support neural network training.

Qualifications

• Master’s or PhD in Computer Science, Robotics, Engineering, or a related field.
• Experience at autonomous driving or humanoid robotics companies on physics simulation.
• Hands-on experience deploying and debugging neural network models on robotic hardware.
• Expertise in reinforcement learning and neural network training.
• Demonstrated Tech Lead experience, coordinating a team of robotics engineers and driving projects from conception to deployment.
• Contributions to popular open-source simulation frameworks or research publications in top-tier conferences (e.g., ICRA, IROS, RSS, CoRL).

Pay

Base salary range: 224,000 USD – 356,500 USD. You will also be eligible for equity and benefits.