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

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 Qualifications 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 #J-18808-Ljbffr