Senior Dense Linear Algebra Engineer - CUDA & GPUs (Remote)

NVIDIA Corporation; Santa Clara (CA); On-site; USD 184,000 - 357,000; Full time

Benefits offered by this job

Equity

Benefits

Job summary

NVIDIA Corporation in Santa Clara seeks a Senior Math Libraries Engineer to design, implement and optimize dense linear algebra kernels for cuSOLVER on GPUs, collaborating with multiple teams.

You will lead efforts in high-performance numerical software, work with CUDA, MPI and OpenMP, and contribute to library roadmaps and maintainability. This role demands deep math expertise and shipping scalable HPC libraries for AI and scientific computing.

Qualifications

• PhD or MSc in Computational Science and Engineering, Computer Science, Applied Mathematics, or related field (or equivalent).
• 5+ years of experience in developing, debugging and optimizing high-performance numerical linear algebra software using C++ and parallel programming (CUDA, MPI, OpenMP, OpenACC, pthreads).
• Strong fundamentals in numerical methods, linear algebra, solvers and decompositions.
• Experience with dense linear algebra libraries such as BLAS, LAPACK and parallelizers like PBLAS/SCALAPACK.
• Collaborative, communicative, and well-documented work style.

Responsibilities

• Design, implement, and optimize scalable high-performance numerical dense linear algebra software on GPUs.
• Provide technical leadership to library engineers, QA engineers, and interns.
• Work with product management to understand feature requirements and roadmaps, improving quality and maintainability.

Skills

C++ programming

Parallel programming

Numerical linear algebra

High-performance computing

CUDA programming

Education

PhD or MSc in Computational Science & Engineering / Computer Science / Applied Mathematics

Tools

CUDA

MPI

OpenMP

OpenACC

pthreads

Job description

NVIDIA Corporation in Santa Clara seeks a Senior Math Libraries Engineer to design, implement and optimize dense linear algebra kernels for cuSOLVER on GPUs, collaborating with multiple teams.

You will lead efforts in high-performance numerical software, work with CUDA, MPI and OpenMP, and contribute to library roadmaps and maintainability. This role demands deep math expertise and shipping scalable HPC libraries for AI and scientific computing.