Senior Performance Software Engineer, Deep Learning Libraries

Requirements:

• 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

Nice to Haves:

• Tuning BLAS or deep learning library kernel code

• CUDA/OpenCL GPU programming

• Numerical methods and linear algebra

• LLVM, TVM tensor expressions, or TensorFlow MLIR

What you'll be doing:

• 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

Perks and Benefits:

• NVIDIA is widely considered to be one of the technology world’s most desirable employers

• If you're creative, autonomous, and love a challenge, consider joining our Deep Learning Library team and help us build the real-time, cost-effective computing platform driving our success in this exciting and quickly growing field