GPU Kernel Engineer

Sciforium is seeking a GPU Kernel Engineer to design and optimize custom GPU kernels for next-generation large-scale AI systems. The role spans low-level kernel development and integration into high-level ML frameworks, with a focus on improving performance for large-scale training and inference.

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
• Work closely with hardware vendors (NVIDIA/AMD) and stay current on the latest GPU architecture capabilities and compiler/toolchain improvements
• Contribute to tooling, documentation, benchmarking suites, and testing frameworks to ensure correctness and performance reproducibility