Senior Math Libraries Engineer - Dense Linear Algebra at NVIDIA

Santa Clara, California, United States

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Not SpecifiedCompensation

Senior (5 to 8 years)Experience Level

Full TimeJob Type

UnknownVisa

AI, Scientific Computing, AutomotiveIndustries

Requirements

PhD or MSc degree in Computational Science and Engineering, Computer Science, Applied Mathematics, or related science/engineering field (or equivalent experience)
5+ years of experience in developing, debugging, and optimizing high-performance numerical linear algebra software using C++
Experience with CUDA, MPI, OpenMP, OpenACC, pthreads
Strong fundamentals in numerical methods, including computational linear algebra, linear system solvers, and decompositions
Experience with dense linear algebra libraries such as BLAS, LAPACK; and their parallel counterparts like PBLAS and SCALAPACK
Strong collaboration, communication, and documentation habits

Responsibilities

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 closely with product management and partners to understand requirements and contribute to technical roadmaps
Identifying and implementing improvements to library quality, performance, and maintainability through re-architecting and innovative practices

Skills

Key technologies and capabilities for this role

C++CUDAMPIOpenMPOpenACCpthreadsNumerical Linear AlgebraDense Linear AlgebraGPU ProgrammingHigh-Performance Computing

Questions & Answers

Common questions about this position

Is this position remote?

Yes, the position is remote.

What is the salary for this role?

This information is not specified in the job description.

What skills and experience are required for this Senior Math Libraries Engineer role?

Required qualifications include a PhD or MSc in a relevant field, 5+ years developing high-performance numerical linear algebra software with C++, experience with CUDA, MPI, OpenMP, OpenACC, pthreads, strong numerical methods knowledge, and experience with libraries like BLAS, LAPACK, PBLAS, and SCALAPACK.

What does the team collaboration look like in this role?

You will collaborate with other developers, provide technical leadership to library engineers, QA engineers, and interns, work closely with product management and partners, and demonstrate strong collaboration, communication, and documentation habits.

What makes a candidate stand out for this position?

Candidates stand out with knowledge of CPU/GPU hardware architecture, experience with CI/CD systems and tools like JIRA, experience in globally distributed organizations, and a strong background in large-scale computing technologies like PDE solvers and eigenvalue solvers.

NVIDIA

Designs GPUs and AI computing solutions

About NVIDIA

NVIDIA designs and manufactures graphics processing units (GPUs) and system on a chip units (SoCs) for various markets, including gaming, professional visualization, data centers, and automotive. Their products include GPUs tailored for gaming and professional use, as well as platforms for artificial intelligence (AI) and high-performance computing (HPC) that cater to developers, data scientists, and IT administrators. NVIDIA generates revenue through the sale of hardware, software solutions, and cloud-based services, such as NVIDIA CloudXR and NGC, which enhance experiences in AI, machine learning, and computer vision. What sets NVIDIA apart from competitors is its strong focus on research and development, allowing it to maintain a leadership position in a competitive market. The company's goal is to drive innovation and provide advanced solutions that meet the needs of a diverse clientele, including gamers, researchers, and enterprises.

Santa Clara, CaliforniaHeadquarters

1993Year Founded

$19.5MTotal Funding

IPOCompany Stage

Automotive & Transportation, Enterprise Software, AI & Machine Learning, GamingIndustries

10,001+Employees

Benefits

Company Equity

401(k) Company Match

Risks

Increased competition from AI startups like xAI could challenge NVIDIA's market position.

Serve Robotics' expansion may divert resources from NVIDIA's core GPU and AI businesses.

Integration of VinBrain may pose challenges and distract from NVIDIA's primary operations.

Differentiation

NVIDIA leads in AI and HPC solutions with cutting-edge GPU technology.

The company excels in diverse markets, including gaming, data centers, and autonomous vehicles.

NVIDIA's cloud services, like CloudXR, offer scalable solutions for AI and machine learning.

Upsides

Acquisition of VinBrain enhances NVIDIA's AI capabilities in the healthcare sector.

Investment in Nebius Group boosts NVIDIA's AI infrastructure and cloud platform offerings.

Serve Robotics' expansion, backed by NVIDIA, highlights growth in autonomous delivery services.

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