GPU Math Libraries Engineer: AI & HPC Emulation

NVIDIA; Clermont-Dessous; Hybrid; EUR 85,000 - 130,000; Full time

Job summary

NVIDIA is seeking software engineers to join our math libraries teams for AI and HPC kernel generation, focusing on emulation of math operations across precisions. You will design and optimize CUDA/C++ libraries, collaborating with global teams to meet demanding performance goals.

Join a world‑class group driving GPU-accelerated math libraries used in AI, NLP, and scientific computing, with opportunities to mentor interns and influence technical roadmaps across products.

Qualifications

• PhD or Master's degree in Computer Science, Applied Math, or related science or engineering field (or equivalent).
• 5+ years of experience in designing, developing, testing, maintenance, and performance optimization of production software using CUDA and C++.
• Good knowledge of GPU hardware architecture.
• Strong fundamentals in finite precision arithmetics and numerical methods for linear algebra.
• Great teamwork, communication, and documentation habits.

Responsibilities

• Scoping, designing, and implementing high quality and performance numerical dense linear algebra software on GPUs.
• Providing technical leadership and feedback to library engineers working with you on projects and sometimes mentor interns.
• Working closely with product management and other internal and external customers to understand feature and performance requirements and help define the technical roadmaps of libraries.
• Finding opportunities to improve library performance and reduce code maintenance overhead through re-architecting.

Skills

CUDA

C++

GPU architecture

Numerical methods

Finite precision arithmetic

Education

PhD or Master’s in CS/Applied Math

Tools

CUTLASS

Python

Job description

NVIDIA is seeking software engineers to join our math libraries teams for AI and HPC kernel generation, focusing on emulation of math operations across precisions. You will design and optimize CUDA/C++ libraries, collaborating with global teams to meet demanding performance goals.

Join a world‑class group driving GPU-accelerated math libraries used in AI, NLP, and scientific computing, with opportunities to mentor interns and influence technical roadmaps across products.