ML Compiler and Systems Engineer (Bay Area / Paris / Remote)

Job not on LinkedIn

August 9

🏄 California – Remote

Although this job is listed in California, this company may be open to hiring remote in other states.

⏰ Full Time

🟡 Mid-level

🟠 Senior

⚙️ Systems Engineer

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Genesis AI

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AI • Robotics • Research

Genesis AI is a global physical AI lab and full-stack robotics company. We build generalist robots to unlock unlimited physical labor, allowing humans to focus on creativity and curiosity. With a vision founded on a scalable data engine, an open-source ecosystem, and robust robot deployments, we aim to train a universal robotics foundation model for controlling any robot in any task. Our diverse team comprises leading minds in robotics and AI, dedicated to advancing the field and addressing complex challenges in real-world environments.

11 - 50 employees

📋 Description

• 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

🎯 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