Simulation Infrastructure
San Francisco, CAFull-timePosted 4mo agoStill listed 1w ago
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At a glance
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Job overview
The role focuses on building core simulation infrastructure for robotics model development, designing scalable systems to create and manage diverse simulation workloads, and developing reusable environment frameworks and tooling. Collaboration spans policy training, asset generation, and a team dedicated to advancing general-purpose Physical AI, emphasizing physics simulation expertise and GPU programming.
Skills & qualifications
Skills
Full job description
What You’ll Do
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Build core simulation-centered infrastructure for robotics model development, evaluation, and iteration.
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Design scalable systems for creating, running, and managing diverse simulation workloads across tasks, environments, and robots.
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Develop reusable environment frameworks, task interfaces, and tooling that make simulation workflows more reliable and observable.
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Work with the policy training team to bridge the sim-to-real gap
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Develop a real-to-sim pipeline in collaboration with the asset generation team
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Collaborate with a team of driven individuals committed to building general-purpose Physical AI
What You’ll Bring
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Passion for your craft and demonstrated excellence in physics simulation engineering
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Exceptional ownership and initiative: finding and solving problems independently
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Extensive experience in physics simulation, with a preference for expertise in rigid body simulation and FEM
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Insights and requests from a robotic researcher/engineer’s perspective for improving user experience
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Proficiency in CUDA and GPU programming
Bonus Points
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Built closed-loop or log-replay evaluation at scale.
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Experience with robotics simulation tools such as genesis-world, Isaac Sim, MuJoCo, Newton, Drake, Gazebo, or similar platforms.
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Experience with synthetic data, scene generation, asset pipelines, sim-to-real, or robotics benchmarks.
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Experience with robot manipulation, mobile manipulation, humanoids, or embodied AI systems.
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