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Nvidia Senior Math Libraries Engineer - Sparse Linear Algebra 
United States, Texas 
887318612

15.10.2025
US, CA, Santa Clara
US, Remote
time type
Full time
posted on
Posted 25 Days Ago
job requisition id

In this role, you will work together with other developers on designing, developing, and optimizing kernels for various algorithms including basic sparse BLAS operations likematrix-vector-productsandmatrix-matrix-products,


What you will be doing:

  • Designing, implementing and optimizing scalable high-performance numerical sparse linear algebra software for existing and future GPU architectures

  • Working with library engineers, QA engineers, and interns on topics ranging from sparse BLAS operations to advanced direct and iterative sparse solvers

  • Working closely with product management and other internal and external partners to understand feature and performance requirements and contribute to the technical roadmaps of libraries

  • Finding and realizing opportunities to improve library quality, performance and maintainability through re-architecting and establishing innovative software development practices

What we need to see:

  • PhD or MSc degree (or equivalent experience) in Computational Science and Engineering, Computer Science, Applied Mathematics, or related science or engineering field is preferred

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

  • Strong fundamentals in floating point arithmetic and implementation of sparse linear algebra primitives like matrix-vector and matrix-matrix products

  • Experience in developing , maintaining, and testing sparse linear algebra libraries

  • Strong collaboration, communication, and documentation habits.

Ways to stand out from the crowd:

  • Good knowledge of CPU and/or GPU hardware architecture and low-level GPU performance optimization

  • Familiarity with technologies such as multi-frontal factorizations, iterative solvers, preconditioners, and algebraic multigrid

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

  • Understanding of large-scale computing technologies such as PDE solvers, eigenvalue solvers and time-domain simulation methods (e.g., CFD, FEA)

  • Working experience in a globally distributed and agile organization

You will also be eligible for equity and .