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About the Role
As a core maintainer of Genesis-World, you will build the software engineering backbone of this open-source simulation platform for physical AI. Your focus will be on making the codebase reliable, maintainable, and frictionless, directly impacting the adoption and usability for roboticists worldwide.
Responsibilities
- Build the software engineering backbone of Genesis-World, ensuring reliability, maintainability, and a frictionless user experience.
- Act as a core maintainer with shared stewardship of the entire platform.
- Collaborate with the physics team to enhance infrastructure, tooling, APIs, and architecture.
- Make any bug reproducible by implementing bit-exact dump and reload capabilities across different machines and backends.
- Develop automatic reproduction scripts for any failing simulation run.
- Enhance the autodiff capabilities of Genesis-World, focusing on memory efficiency, performance, and maintainability.
- Drive requirements for the Quadrants JIT compiler to improve autodiff integration.
- Enable editing scenes at frozen time for instant iteration on layout without full builds.
- Develop first-class plugins for physics solvers and interactive viewer backends, generalizing sensor extensibility.
- Implement clean abstractions for motors and MIMO transmissions at the interface between users and the physics engine.
- Decouple the clock and timestep from global engine scope to allow for independent environment stepping and adaptive timesteps.
- Implement physics-triggered events to make scenes more dynamic.
- Refactor legacy subsystems, strengthen typing, ensure consistent coding style, reduce Python overhead on hot paths, implement full scene serialization, and enhance telemetry and replay.
- Review issues and pull requests with the core team.
- Answer questions from users and contributors.
- Participate in adoption initiatives.
Requirements
- Strong Python engineering experience on large codebases, including architecture, refactoring, typing, packaging, and performance profiling.
- Experience with developer tooling, test infrastructure, or CI at scale.
- Fluency with JIT compilation, code generation, or GPU computing stacks to reason about compilation caching, kernel dispatch, and startup costs.
- Ability to debug across a full platform matrix: Windows, Linux, and macOS, on x86 and arm64, over CUDA, AMD, and Apple Metal.
- Experience with open-source practices, including triaging issues, reviewing external pull requests, and community communication.
- Comfort with physics and robotics concepts to understand simulator functionality and usage.
- A strong focus on the engineer's experience, proactively identifying and removing friction points like slow tests or cryptic errors.
Skills
- Python
- JIT compilation
- Code generation
- GPU computing
- Performance profiling
- Developer tooling
- Test infrastructure
- CI/CD
- API design
- Physics
- Robotics
- Open-source contribution
- Debugging
- Large codebases
- Refactoring
- Typing
- Packaging
- CUDA
- AMD
- Apple Metal
- Windows
- Linux
- macOS
- x86
- arm64
Location
- Remote
Work Type
- Full-time
- Open-source
Experience Level
- Core maintainer
About the Company
- Genesis AI is building Genesis-World, an open-source, general-purpose simulation platform for physical AI. The platform features a unified multi-physics engine, a real-time photorealistic renderer (Nyx), diverse sensor simulation, and an advanced Incremental Potential Contact solver. It is Python-first, runs on multiple hardware backends via an in-house JIT compiler (Quadrants), and enables massively batched GPU simulation for large-scale learning. Genesis AI's strategy leverages simulation to overcome the evaluation bottleneck in robotics, aiming for physical AI that improves at the speed of compute.