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Senior Math Libraries Engineer - Sparsity in AI

NVIDIA· Engineer, Sys SW
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Santa Clara, CA, Hybrid (Remote - US)$184k - $287.5kFull-timePosted 7mo ago

About the role

Software engineer role focused on design and development of GPU-accelerated libraries and tools for unstructured sparsity in DL and HPC, with emphasis on C++, Python, and CUDA, targeting NVIDIA GPUs and integration with DL frameworks like PyTorch.

Responsibilities

  • 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 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

Qualifications

  • 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

Skills

Required:C++PythonCUDAParallel programmingDomain-specific language designCommunication and collaboration
Nice to have:DL frameworksNumerical linear algebra

Benefits

  • You will also be eligible for equity and benefits
Last updated Jul 3, 2026. Interested? Apply on the company site.

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