GPU Kernel Optimization Expert | CUDA/HIP | C++17 | Profiler-Guided Performance

We are seeking experienced GPU kernel optimization specialists to work on a cutting-edge AI project with a leading AI lab. RESPONSIBILITIES: - Analyze and optimize GPU kernels for performance, efficiency, and hardware utilization - Use profiler metrics (L2 cache hit rate, L2 throughput, occupancy) to guide kernel improvements - Write, modify, and reason about C++17, Python, and GPU programming code - Apply CUDA, HIP, or related kernel programming expertise to improve performance - Document optimization decisions clearly REQUIREMENTS: - Fluent in C++ through C++17 - Working knowledge of Python and Git - Fluent in at least one GPU programming model: CUDA, HIP, HLSL, GLSL, or similar - 1+ year professional or graduate-level GPU experience - Strong understanding of GPU profiler metrics (NSight Compute is a plus) - Available 20+ hrs/week NICE TO HAVE: - Experience with CUDA C++ Core Libraries, inline PTX assembly, or tensor core optimization - Experience optimizing kernels for NVIDIA Blackwell hardware - Open-source contributions related to GPU kernel optimization Rate: $80-100/hr | Remote | Contract