Genesis-World: Core Physics Engineer

<h2>What we're building</h2><p style="min-height:1.5em">Robots will learn in simulation before they hit the factory. Genesis-World is our bet on that future.</p><p style="min-height:1.5em"><a target="_blank" rel="noopener noreferrer nofollow" href="https://github.com/Genesis-Embodied-AI/genesis-world">Genesis-World</a> is an open-source, general-purpose simulation platform for physical AI from <a target="_blank" rel="noopener noreferrer nofollow" href="https://www.genesis.ai/">Genesis AI</a>. One unified multi-physics engine: rigid bodies, FEM, MPM, particles, cloth, fluids. A robot arm can pour water onto sand, grasp a deformable object, or cut a soft body, all in the same simulation. Nyx, our in-house renderer, may be the most promising renderer for robotics out there: real-time photo-realistic rendering, advanced features like depth of field, and state-of-the-art techniques never seen before. Sensors of every kind: cameras, lidar, IMU, contact forces, temperature, plus arguably the most advanced tactile simulation available (<a target="_blank" rel="noopener noreferrer nofollow" href="https://openreview.net/forum?id=md8q2kfZHP">paper</a>). And the engine keeps growing: we are developing internally the most comprehensive and fastest Incremental Potential Contact (<a target="_blank" rel="noopener noreferrer nofollow" href="https://ipc-sim.github.io">paper</a>) solver for deformable body dynamics we know of, soon to be open-sourced. It powers real business applications, from full-fledged box packaging with labelling machine and all, to wire harnessing and lab automation, without any physics hack or compromise.</p><p style="min-height:1.5em">Everything is Python-first and runs anywhere. Kernels are written once, and Quadrants, our in-house JIT compiler, lowers them to CUDA, AMD ROCm, Apple Metal, Vulkan, x86, and ARM64. A single laptop or a datacenter. Massively batched GPU simulation for learning at scale, and complex non-batched scenes where CPU wins outright.</p><p style="min-height:1.5em">This is at <a target="_blank" rel="noopener noreferrer nofollow" href="https://www.genesis.ai/blog/the-role-of-simulation-in-scalable-robotics-genesis-world-10-and-the-path-forward">the core of Genesis AI's strategy</a>. Evaluation is the bottleneck of scalable robotics: real hardware caps iteration at wall-clock time, but simulation turns it into a compute problem. Ours already runs two orders of magnitude faster than hardware (tens of thousands of episodes in half an hour instead of 200+ hours), while correlating with on-hardware rollouts at 89%. The north star: physical AI that improves at the speed of compute.</p><p style="min-height:1.5em"></p><h2>The role</h2><p style="min-height:1.5em">You push the physics of Genesis-World forward. The mandate is clear: ship production-ready simulation capabilities that matter for the company's internal needs. Research applied end-to-end, from algorithm to merged, tested, documented code that real robot-learning pipelines depend on. Occasional groundbreaking research happens, notably through academic collaborations. But the core of the job is making the engine measurably better along five axes:</p><ul style="min-height:1.5em"><li><p style="min-height:1.5em"><strong>Speed.</strong> Algorithms that are not only faster but also smart enough to spend compute only where it matters across both time and space: larger stable timesteps, selective fidelity (adaptive across scales or simply hand-set), structure-aware solvers.</p></li><li><p style="min-height:1.5em"><