Senior Engineer, Math Libraries - Consumer and Embedded Platforms

We are looking for a Senior Software Engineer to join our team enabling CUDA Math Libraries on new and specialized platforms. Around the world, leading commercial and academic organizations are revolutionizing AI, data analytics, and scientific and engineering simulations using data centers powered by GPUs. NVIDIA’s math libraries are core to global AI infrastructure and must deliver functionality and performance on every target.

In this role, you will enable NVIDIA’s CUDA Math Libraries on a wide variety of emerging platforms, including integration, functional qualification, compliance, and performance readiness, working closely with the core library and devops engineering teams to ensure consistent, high-quality support on every expanding platform. Ideal candidates will have experience in scientific and numerical computing libraries, GPU kernel development, and parallel programming.

This is your opportunity to join an organization that is on the forefront of unlocking application performance in the AI era! We would love for you to bring your talent to the team.

What You’ll Be Doing:

• Ensure platform readiness across Math Libraries (including cuBLAS, cuSPARSE, cuSOLVER, cuFFT, and others) for new and specialized platforms.
• Perform defect triage and isolation of platform-specific versus library-specific problems, fixing bugs to ensure functional correctness and referring to a library specialist as needed.
• Identify performance targets for new platforms, establish performance testing and fix performance regressions.
• Collaborate with CI/CD, build, and test infrastructure teams to establish platform-specific qualification and validation pipelines.

What We Need to See:

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

5+ years of overall experience in developing high-performance numerical software.

Experience with object-oriented programming, large system software architecture development, parallel computing, testing, maintenance, and performance optimization of HPC software using C++ and Python.

Strong understanding of fundamental numerical methods and computations in science, engineering, and/or deep learning.

Strong communication, collaboration, and documentation habits.

Experience with software development practices, such as CI/CD systems, and project management tools such as JIRA.

Ways to Stand Out from the Crowd:

Experience with CUDA, GPU-accelerated computing, and parallel programming (e.g. MPI, OpenMP, OpenACC, pthreads).

Familiarity with math libraries (BLAS, LAPACK, FFT, sparse solvers).

Proven track record using Agentic AI to boost your efficiency and code quality.