GPU Programming Expert - Fully Remote | Upto $120/hr

Mercor connects elite creative and technical talent with leading AI research labs. Headquartered in San Francisco, our investors include Benchmark , General Catalyst , Peter Thiel , Adam D'Angelo , Larry Summers , and Jack Dorsey . Position: CUDA Engineering Expert Type: Contract Compensation: $80–$120/hour Location: Remote Role Responsibilities Analyze and optimize GPU kernels for performance, efficiency, and hardware utilization. Use profiler metrics like L2 cache hit rate , L2 throughput , and occupancy to guide kernel improvements. Review GPU kernel implementations to identify bottlenecks without needing extensive algorithmic background. Write, modify, and reason about C++17 , Python , and GPU programming code. Apply CUDA , HIP , and shader programming expertise to improve performance outcomes. Document optimization decisions clearly, noting when specific profiler metrics are useful. Qualifications Must-Have Available to work at least 20 hrs/wk . Fluent in core C++ features through C++17 . Working knowledge of Python and Git . Fluent in at least one GPU programming model like CUDA , HIP , Slang , HLSL , or GLSL . At least 1 year of professional or graduate-level research experience with GPUs . Strong understanding of GPU profiler performance metrics for kernel optimization. Ability to optimize GPU kernels without deep prior context on every algorithm. Preferred Experience with CUDA , HIP , CUDA C++ Core Libraries , inline PTX assembly, or tensor core-level optimization. Experience optimizing kernels for NVIDIA Blackwell hardware . Familiarity with NSight Compute . Prior experience with GPU hardware organizations like NVIDIA , AMD , or Qualcomm . Open-source contributions related to GPU kernel optimization . #J-18808-Ljbffr mercor