- Robot type
- Robot AI and Software
- Location
- San CarlosCaliforniaUSA
- Job type
- Artificial Intelligence
- Posted
- Aug 18, 2026
Genesis-World: Core Physics Engineer
Job description
Robots will learn in simulation before they hit the factory. Genesis-World is our bet on that future.
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.
This is at the core of Genesis AI's strategy . Evaluation is the bottleneck of scalable robotics: real hardware caps iteration at wall-clock time, but simulation turns it into a compute problem.
Genesis-World is an open-source, general-purpose simulation platform for…
Job responsibilities
- Speed. 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…
- Completeness. No physics off limits: water, human animation, air flow, gravel, tendons, even body organs. Whatever the next use-case needs, the engine grows to cover it.
- Fidelity. More realistic models: contact, friction, deformation, energy, actuation, materials…
- Versatility. Extensible multi-physics without compromise on realism: all solvers in the scene coupled together at once, two-way and constraint-based.
- Scalability. From workstation to factory scale, and one day, city scale: thousands of interacting entities, batched across environments, without losing physical soundness.
Job requirements
- A strong background in physics-based simulation, preferably related to robotics: RBD, FEM, MPM, SPH, IPC, XPBD, VBD, ABD, plus constrained optimization and numerical integration of stiff systems.
- A track record of shipping simulation code that others rely on, in an engine, in industry, or in a research codebase used beyond its authors.
- Solid HPC programming (CPU and/or GPU), and an instinct for what makes a numerical method fast in practice, beyond complexity classes.
- Rigor in validation: analytical closed forms, cross-engine consistency, real-world data.
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