Senior Math Libraries Engineer - Sparsity in AI

We are looking for software engineers to contribute to the design and development of libraries and tools to simplify and accelerate computing for unstructured sparsity in DL and HPC. The ideal candidate will have experience developing accelerated computing software and be motivated to advance the state-of-the-art in a variety of accelerated computing domains and DL frameworks like PyTorch.

Requirements

• 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
• 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

Benefits

• Eligible for equity and benefits