- San Francisco, California, United States
- On-site
- Full-time · Senior
- 5+ years
We are seeking a highly skilled GPU Kernel Engineer who is passionate about pushing the limits of performance on modern accelerators. This involves designing and optimizing custom GPU kernels that power next-generation large-scale AI systems.
Compensation
Competitive salary and equity
Responsibilities
- Design, implement, and optimize custom GPU kernels using C++, PTX, CUDA, ROCm, Triton, and/or JAX Pallas.
- Profile and optimize end-to-end performance of ML operations, with a focus on large-scale LLM training and inference.
- Integrate low-level GPU kernels into frameworks such as PyTorch, JAX, and custom internal runtimes.
- Develop performance models, identify bottlenecks, and deliver kernel-level improvements that significantly accelerate AI workloads.
- Collaborate with ML researchers, distributed systems engineers, and model-serving teams to optimize compute performance across the stack.
Requirements
- Bachelor’s
- Master’s
- PhD
- Computer Science
- Computer Engineering