Senior Research Engineer, Simulation
NVIDIA, US, CA, Santa Clara
- Pay
- Not listed by the employer
- Work type
- Not stated
- Level
- Senior
- Area
- Research, Inference & ML systems, ML / AI engineering
- Posted
- 9 days ago
About the role
NVIDIA is searching for a senior or principal engineer who specializes in physics simulation in the Generalist Embodied Agent Research (GEAR) group. Our team is leading Project GR00T, NVIDIA’s moonshot initiative at building foundation models and full-stack technology for humanoid robots.
You will work with an amazing and collaborative research team that consistently produces influential works on multimodal foundation models, large-scale robot learning, embodied AI, and physical simulation. Our past projects include Eureka, VIMA, Voyager, MineDojo, MimicPlay, Prismer, and more. Your contributions will have a significant impact on our research projects and product roadmaps.
What you will be doing:
- 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.
What we need to see:
- Bachelor’s degree or above in Computer Science, Robotics, Engineering, or a related field;
- 10+ years of full-time industry experience on 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, such as 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.
Ways to stand out from the crowd:
- Master’s or PhD’s degree in Computer Science, Robotics, Engineering, or a related field;
- Experience at autonomous driving or humanoid robotics companies on physics simulation;
- Hands-on experience with deploying and debugging neural network models on robotic hardware;
- Expertise at 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, such as ICRA, IROS, RSS, CoRL.
NVIDIA is widely considered to be one of the technology world's most desirable employers. We have some of the most forward-thinking and productive people in the world. Please join us and be part of the forefront of developing general-purpose robots and large-scale foundation models!
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Listed on NVIDIA's Workday careers site; checked 27 h ago. First seen by us 28 h ago. Being listed doesn't mean the team is actively interviewing.