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Genesis AI

Robot type
Robot AI and Software
Location
San CarlosCaliforniaUSA
Job type
Artificial Intelligence
Posted
Aug 18, 2026
Full-time

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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