GPU Kernel Engineer

About the role

Sciforium is an AI infrastructure company developing multimodal AI models and a high-efficiency serving platform. The company is seeking a GPU Kernel Engineer to design and optimize custom GPU kernels for large-scale AI systems, integrate optimized operations into machine learning frameworks, and improve performance across the hardware-software stack. The role involves collaborating with researchers, systems engineers, model-serving teams, and hardware vendors to enhance the efficiency and scalability of AI workloads.

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