GPU-accelerated computing • artificial intelligence • deep learning • virtual reality • gaming
10,000+
September 15
GPU-accelerated computing • artificial intelligence • deep learning • virtual reality • gaming
10,000+
• Writing highly tuned compute kernels, mostly in C++ CUDA, to perform core deep learning operations (e.g. matrix multiplies, convolutions, normalizations) • Following general software engineering best practices including support for regression testing and CI/CD flows • Collaborating with teams across NVIDIA: CUDA compiler team on generating optimal assembly code Deep learning training and inference performance teams on which layers require optimization Hardware and architecture teams on the programming model for new deep learning hardware features
• PhD degree or equivalent experience in Computer Science, Computer Engineering, Applied Math, or related field or a Bachelors or Masters degree plus 4-6 years of equivalent relevant industry experience. • Demonstrated strong C++ programming and software design skills, including debugging, performance analysis, and test design. • Experience with performance-oriented parallel programming, even if it’s not on GPUs (e.g. with OpenMP or pthreads) • Solid understanding of computer architecture and some experience with assembly programming
Apply NowJuly 11
201 - 500