Shanghai, CHN
5 days ago
Senior Solutions Architect, Simulation
NVIDIA accelerates humanoid robots’ development with the Isaac solution and GR00T blueprint. We’re now looking for a robotics expert, especially in simulation to support this effort. As a Solutions Architect, you’ll collaborate with an exceptional and highly collaborative research team known for influential work in multimodal foundation models, large-scale robot learning, embodied AI, and physics simulation, pushing the frontier of humanoid robotics. 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 in Computer Science, Robotics, Engineering, or a related field; + 3+ years of full-time industry experience on robotics and/or physics simulation; + Proficiency in languages such as Python, C++, and 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 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.
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