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NVIDIA

Designs the chips and software that power AI

Engineering Manager - Math Libraries, Consumer and Embedded Platforms

Engineering LeadershipConfirmed live in the last 24 hours
Full-time

About the Job

Requirements

  • A PhD or MSc degree in Computational Science and Engineering, Computer Science, Applied Mathematics, or a related science or engineering field, or equivalent experience.
  • At least 8 years of overall experience developing high-performance numerical software.
  • At least 3 years leading and mentoring software engineering teams.
  • Hands-on experience with object-oriented programming, large system software architecture development, parallel computing, testing, maintenance, and performance optimization of high-performance computing software using C++ and Python.
  • Strong understanding of fundamental numerical methods and computations in science, engineering, and/or deep learning.
  • Experience with software development practices such as continuous integration and continuous delivery systems and project management tools such as JIRA.

Responsibilities

  • Lead, mentor, and develop the team.
  • Own end-to-end platform readiness across Math Libraries for specialized platforms, including integration, functional qualification, and compliance.
  • Collaborate with continuous integration and continuous delivery, build, and test infrastructure teams to establish platform-specific qualification and validation pipelines.
  • Perform defect triage and isolation of platform-specific versus library-specific problems, fix bugs to ensure functional correctness, and refer issues to a library specialist as needed.
  • Identify performance targets for new platforms, establish performance testing, and fix performance regressions.
  • Define and deliver a technical roadmap for platform readiness that scales with the number and complexity of supported platforms.
  • Coordinate dependencies across library teams, CUDA, compilers, quality assurance, release processing, and platform organizations with product, engineering, and program managers.

Desired Qualifications

  • Experience with CUDA, GPU-accelerated computing, and parallel programming such as MPI, OpenMP, OpenACC, or pthreads.
  • Familiarity with math libraries such as BLAS, LAPACK, FFT, and sparse solvers.
  • A proven track record using agentic artificial intelligence to improve efficiency and code quality.
  • Experience with cross-platform software development and platform bring-up across multiple architectures.
  • Experience delivering software for safety-critical or embedded environments, such as DriveOS or ISO 26262.

About the Company

NVIDIA

Designs the chips and software that power AI

NVIDIA designs the chips and software that power artificial intelligence and sells complete data center systems to cloud providers, AI labs, and other businesses, along with GeForce graphics cards for gamers. Its GPUs, chips that perform thousands of calculations at once, became the main hardware for AI after researchers used them to train the AlexNet image-recognition model in 2012. NVIDIA connects many GPUs with its own processors and networking gear into servers and rack-sized computers, and developers program them through its CUDA software. These systems bring in most of its sales, and it also makes chips for cars and robots. Jensen Huang co-founded NVIDIA in 1993, and it is based in Santa Clara, California.

Company size
10,001+
Company stage
IPO
Headquarters
Santa Clara, CA
Founded
1993

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