Simulation Infrastructure — Genesis AI

Genesis AI, a robotics company developing general-purpose Physical AI, is hiring a Simulation Infrastructure engineer in London to build core simulation-centered infrastructure for robotics model development, evaluation, and iteration. The role involves designing scalable systems for simulation workloads, developing reusable environment frameworks, and bridging the sim-to-real gap, with a preference for expertise in rigid body simulation, FEM, CUDA, and GPU programming.

Simulation Infrastructure - Salary - Not published - Location - London - Work type - Hybrid - Posted - today Apply on company site opens in new tab https://jobs.ashbyhq.com/genesis/d57a59b9-ae1d-46ab-b2c4-a05b3e0f3daa/application 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.