ML Compiler and Systems

What You'll Do - 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 You’ll Bring - 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