Member of Technical Staff, ML Compiler and Systems (Bay Area, Remote)

Genesis AI • San Carlos, CA

5d • Remote

About The Position

This role focuses on advancing a high-performance robotics simulation platform. The individual will be responsible for designing and implementing the compute infrastructure and data flow mechanisms essential for optimizing physics simulation and foundation model training. A key aspect of the role involves leading the development of the compiler stack, with a specific emphasis on JIT compilation, LLVM IR, and GPU codegen to enhance both compile and runtime performance. The position also requires collaboration to improve the compiler's support for differentiable programming, which is vital for training neural networks within simulations. The role involves staying abreast of the latest advancements in ML compilers (e.g., torch, Triton, JAX) and applying suitable techniques. Close collaboration with simulation and robotics engineers is expected to ensure compiler enhancements meet application requirements. Additionally, the role encourages contributions to open-source projects and active participation in the compiler and systems community.

Requirements

• Strong background in compiler construction, particularly in JIT compilation and LLVM-based code generation
• Extensive experience with GPU programming models (e.g., CUDA, Vulkan) and understanding of GPU architecture
• Track record as a core contributor to GPU programming infrastructure—such as Torch, JAX, Mojo, Taichi, or Warp
• Proven ability to profile and optimize complex systems for performance and scalability
• Understanding of automatic differentiation and its application in simulation and machine learning contexts
• Excellent communication skills and a collaborative approach to problem-solving
• Enthusiasm for contributing to and engaging with open-source communities

Responsibilities

• Lead the evolution of our high-performance robotics simulation platform
• Design and implement the compute infrastructure and data flow mechanisms to optimize performance for physics simulation and foundation model training
• Lead development of our compiler stack, focusing on JIT compilation, LLVM IR, and GPU codegen to minimize compile time and maximize runtime performance
• Collaborate with the team to improve the compiler's support for differentiable programming, crucial for training neural networks within simulations
• Stay current on state-of-the-art ML compilers—such as those in torch, Triton, and JAX—and decide which techniques and approaches are best suited for our application
• Work closely with simulation and robotics engineers to align compiler enhancements with application needs
• Contribute to relevant open-source projects and participate actively in the broader compiler and systems community

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: No Education Listed