> Markdown version of [/jobs/ext/4554321-simulation-infrastructure](https://www.wearedevelopers.com/jobs/ext/4554321-simulation-infrastructure). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Simulation Infrastructure - **Company:** GENESIS GROUPE - **Location:** Paris, France - **Contract:** Permanent contract - **Skills:** Nvidia CUDA, Gpu Programming, Isaac Sim, Embodied AI - **Published:** November 4, 2026 - **Apply:** https://www.indeed.com/viewjob?jk=ec34f598e94ecfa8 ## About the Role * 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, * 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. ## Description * 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