Drimva

NVIDIA

Senior Engineer, Math Libraries - Consumer and Embedded Platforms

$152K–$288K

US, CA, Santa Clara +5 · Senior · Full-time · Posted Oct 5, 2026

Location
US, CA, Santa Clara
US, TX, Remote
US, NY, Remote
US, WA, Remote
US, CA, Remote
US, MA, Remote
Experience
5+ years overall experience developing high-performance numerical software.
Education
PhD or MSc degree in Computational Science and Engineering, Computer Science, Applied Mathematics, or related science or engineering field (or equivalent experience).

About the job

Enable and qualify NVIDIA CUDA Math Libraries on emerging and specialized platforms, ensuring functional correctness, compliance, and performance readiness.

What you'll do

  • Ensure Math Libraries are ready on new platforms; triage platform- versus library-specific defects and fix bugs.
  • Set performance targets, establish performance testing, and address regressions.
  • Work with CI/CD, build, and test teams on platform-specific qualification and validation pipelines.

What they ask for

  • PhD or MSc in Computational Science and Engineering, Computer Science, Applied Mathematics, or a related science or engineering field (or equivalent experience).
  • 5+ years of experience developing high-performance numerical software.
  • Experience with C++ and Python for HPC software, including object-oriented programming, parallel computing, testing, maintenance, and performance optimization.
  • Strong understanding of numerical methods and computations in science, engineering, and/or deep learning.

Nice to have

  • CUDA, GPU-accelerated computing, parallel programming, or math-library experience.
  • Agentic AI, cross-platform development, or software delivery for safety-critical or embedded environments.

Pay

152,000 USD - 241,500 USD (base salary, Level 3); 184,000 USD - 287,500 USD (base salary, Level 4)

Tools

CUDA, C++, Python, MPI, OpenMP, OpenACC, pthreads, JIRA

AI focus

The role may use Agentic AI to improve efficiency and code quality; NVIDIA also states it uses AI tools in recruiting.

Model-written summary · the original posting is authoritative

First seen Oct 16, 2026 · Last verified Nov 4, 2026 (UTC)