Member of Technical Staff, ML Compiler and Systems; Bay Area

Job Title

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

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