GPU Kernel Engineer
Sciforium, San Francisco, CA
The role
We are seeking a highly skilled GPU Kernel Engineer who is passionate about pushing the limits of performance on modern accelerators. In this role, you will design and optimize custom GPU kernels that power next-generation large-scale AI systems. You will work across the hardware–software stack, from low-level kernel development to integrating optimized ops into high-level ML frameworks used for large-scale training and inference.
This role is ideal for someone who thrives at the intersection of GPU programming, systems engineering, and cutting-edge AI workloads, and who wants to make meaningful contributions to the efficiency and scalability of our ML platform.
What you will do
- 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.