Senior Math Libraries Engineer - Dense Linear Algebra

Posted 9 Days Ago
Be an Early Applicant
6 Locations
In-Office or Remote
184K-357K Annually
Senior level
Artificial Intelligence • Computer Vision • Hardware • Robotics • Metaverse
The Role
Design, implement, and optimize scalable high-performance dense linear algebra kernels for GPUs. Provide technical leadership, collaborate with product and partners, improve performance and quality, and contribute to library roadmaps and development practices.
Summary Generated by Built In

We are looking for software engineers to join our development efforts in the area of dense linear algebra kernels for high-performance libraries such as cuSOLVER. Around the world, leading commercial and academic organizations are revolutionizing AI, data analytics, and scientific and engineering simulations, using data centers powered by GPUs and high-performance linear algebra libraries. Applications of these technologies include computer aided engineering (CAE), electronic design automation (EDA), quantum chemistry, autonomous vehicles, LLMs, computer vision, encryption, and countless others. Did you know our team develops the GPU accelerated libraries and SDKs that help make these possible?

In this role, you will work together with other developers on designing, developing, and optimizing kernels for various algorithms including triangular factorizations, eigenvalue decompositions and singular value decompositions. Ideal candidates will not only have experience developing accelerated computing kernels, but also be motivated to advance the state-of-the-art in a variety of accelerated computing domains. If this sounds exciting, we would love to meet you!

What you will be doing:

  • Designing, implementing and optimizing scalable high-performance numerical dense linear algebra software on GPUs

  • Providing technical leadership and guidance to library engineers, QA engineers, and interns working with you on projects

  • Working closely with product management and other internal and external partners to understand feature and performance requirements and contribute to the technical roadmaps of libraries

  • Finding and realizing opportunities to improve library quality, performance and maintainability through re-architecting and establishing innovative software development practices

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, debugging and optimizing high-performance numerical linear algebra software using C++ and parallel programming; ideally using CUDA, MPI, OpenMP, OpenACC, pthreads

  • Strong fundamentals in numerical methods such as computational linear algebra, linear system solvers, and methods for eigenvalue, singular value, and other decompositions

  • Experience developing dense linear algebra libraries such as BLAS, LAPACK; and their parallel counterparts like PBLAS and SCALAPACK

  • Strong collaboration, communication, and documentation habits

Ways to stand out from the crowd:

  • Good knowledge of CPU and/or GPU hardware architecture

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

  • Experience with working in a globally distributed organization

  • Strong background of large-scale computing technologies such as PDE solvers, eigenvalue solvers and time-domain simulation methods (e.g., CFD, FEA)

NVIDIA’s invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing for science and engineering. More recently, GPU deep learning ignited modern AI — the next era of computing — with the GPU acting as the brain of computers, robots, and self-driving cars that can perceive and understand the world. Today, we are increasingly known as “the AI computing company.” We're looking to grow our company and build our teams with the smartest people in the world! Join us at the forefront of technological advancement.

#LI-Hybrid

Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 184,000 USD - 287,500 USD for Level 4, and 224,000 USD - 356,500 USD for Level 5.

You will also be eligible for equity and benefits.

Applications for this job will be accepted at least until August 9, 2026.

This posting is for an existing vacancy. 

NVIDIA uses AI tools in its recruiting processes.

NVIDIA is committed to fostering an inclusive work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.

Skills Required

  • PhD or MSc in Computational Science and Engineering, Computer Science, Applied Mathematics, or related field (or equivalent experience)
  • 5+ years developing, debugging, and optimizing high-performance numerical linear algebra software using C++ and parallel programming
  • Experience with CUDA, MPI, OpenMP, OpenACC, pthreads
  • Strong fundamentals in numerical methods: computational linear algebra, linear system solvers, eigenvalue and singular value decompositions
  • Experience developing dense linear algebra libraries such as BLAS and LAPACK and parallel counterparts like PBLAS and SCALAPACK
  • Strong collaboration, communication, and documentation habits
  • Knowledge of CPU and/or GPU hardware architecture
  • Experience adopting and advancing CI/CD systems and project management tools such as JIRA
  • Experience working in a globally distributed organization
  • Background in large-scale computing technologies (PDE solvers, eigenvalue solvers, CFD, FEA)

NVIDIA Compensation & Benefits Highlights

The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about NVIDIA and has not been reviewed or approved by NVIDIA.

  • Equity Value & Accessibility Equity awards and a discounted ESPP are highlighted as core parts of total compensation, enabling employees to share in the company’s success. Stock-based compensation and the two-year lookback ESPP are consistently described as especially valuable.
  • Healthcare Strength Health coverage is portrayed as robust, with comprehensive medical, dental, and vision options alongside mental health support and on-site care resources. Employer HSA contributions and wellness perks reinforce the depth of the offering.
  • Retirement Support Retirement programs are depicted as strong, featuring a meaningful 401(k) match with Roth options and support for Mega Backdoor Roth contributions. These elements position long-term savings as a notable advantage of the total rewards package.

NVIDIA Insights

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The Company
HQ: Santa Clara, CA
21,960 Employees
Year Founded: 1993

What We Do

NVIDIA’s invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing. More recently, GPU deep learning ignited modern AI — the next era of computing — with the GPU acting as the brain of computers, robots, and self-driving cars that can perceive and understand the world. Today, NVIDIA is increasingly known as “the AI computing company.”

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