Nvidia Senior Math Libraries Engineer - Sparsity AI 

United States, Texas 

773896522

What you will be doing:

• Design and develop a C++-based system to simplify and accelerate computing for unstructured sparsity in DL and HPC on NVIDIA GPUs

• Enable the system in languages and frameworks that are more commonly used in DL, such as Python and PyTorch

• Evaluate and improve the performance of the system on real-life applications

• Realize opportunities to improve library quality, performance and maintainability by writing effective and well-tested code for production use

• Work closely with product management and other internal and external partners to understand feature and performance requirements and contribute to technical roadmaps

What we need to see:

• BS, MS or PhD degree in Computer Science, Applied Math, or related field (or equivalent experience)

• 6+ years of overall experience in developing, debugging and optimizing high-performance software using C++ and parallel programming; ideally for sparse linear algebra applications and using CUDA, MPI, OpenMP, or equivalent technologies

• Experience with domain-specific language design and compiler optimizations, in particular sparse compilers (MLIR or TACO)

• Excellent C++, Python, and CUDA programming skills

• Strong collaboration, communication, and documentation habits and ideally experience with working in a globally distributed organization

Ways to stand out from the crowd:

• Strong understanding of sparse computations, in particular sparsity in AI and HPC

• Good understanding of LLMs, Deep Learning methods and frameworks

• Experience with low-level GPU performance optimization

• Understanding of numerical linear algebra methods like direct and iterative solvers

• Experience with adopting and advancing, software development practices such as CI/CD systems and project management tools such as JIRA.