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Genesis

Simulation Infrastructure

Posted 11 Days Ago
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Hybrid
London, Greater London, England, GBR
Senior level
Hybrid
London, Greater London, England, GBR
Senior level
Build scalable infrastructure for robotics simulation, including workload management, environment frameworks, task interfaces, evaluation tooling, and real-to-sim pipelines. Collaborate with policy training and asset-generation teams to improve sim-to-real performance. The role requires extensive physics simulation expertise, particularly rigid body simulation or FEM, along with CUDA and GPU programming proficiency. Experience with robotics simulation platforms, synthetic data, asset pipelines, manipulation, humanoids, or embodied AI is advantageous.
The summary above was generated by AI
What You’ll Do
  • Build core simulation-centered infrastructure for robotics model development, evaluation, and iteration.

  • Design scalable systems for creating, running, and managing diverse simulation workloads across tasks, environments, and robots.

  • Develop reusable environment frameworks, task interfaces, and tooling that make simulation workflows more reliable and observable.

  • Work with the policy training team to bridge the sim-to-real gap

  • Develop a real-to-sim pipeline in collaboration with the asset generation team

  • Collaborate with a team of driven individuals committed to building general-purpose Physical AI

What You’ll Bring
  • Passion for your craft and demonstrated excellence in physics simulation engineering

  • Exceptional ownership and initiative: finding and solving problems independently

  • Extensive experience in physics simulation, with a preference for expertise in rigid body simulation and FEM

  • Insights and requests from a robotic researcher/engineer’s perspective for improving user experience

  • Proficiency in CUDA and GPU programming

Bonus Points
  • Built closed-loop or log-replay evaluation at scale.

  • Experience with robotics simulation tools such as genesis-world, Isaac Sim, MuJoCo, Newton, Drake, Gazebo, or similar platforms.

  • Experience with synthetic data, scene generation, asset pipelines, sim-to-real, or robotics benchmarks.

  • Experience with robot manipulation, mobile manipulation, humanoids, or embodied AI systems.

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