CUDA Engineering Expert | Remote

Work SnapshotType: ContractLocation: RemoteCommitment: 10-40 hrs/weekCompensation: $300What You'll Be DoingAnalyze and optimize GPU kernels for performance, efficiency, and hardware utilization.Use profiler metrics such as L2 cache hit rate, L2 throughput, and occupancy to guide kernel improvements.Review GPU kernel implementations and identify bottlenecks.Write, modify, and reason about C++17, Python, and GPU programming code.Apply CUDA, HIP, shader programming, or related kernel programming expertise to improve performance outcomes.Document optimization decisions clearly, including when specific profiler metrics are or are not useful.What We're Looking ForFluent in core C++ features through C++17.Working knowledge of Python and Git.Fluent in at least one GPU programming model, such as CUDA, HIP, Slang, HLSL, GLSL, or related kernel programming.Have strong relevant experience in the domain working with GPUs.Strong understanding of GPU profiler performance metrics and how to use them to optimize kernels.Ability to optimize GPU kernels without needing deep prior context on every algorithm.Application ProcessSubmit your application through the Easy Apply button.Each application will be reviewed against the role requirements.Candidates who meet the requirements will receive an email with the next steps.Follow the instructions provided in the email to complete the remainder of the application process.