Senior Math Libraries Engineer - Sparse 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, High-Performance Computing, Scientific ComputingIndustries

Requirements

PhD or MSc degree (or equivalent experience) in Computational Science and Engineering, Computer Science, Applied Mathematics, or related science or engineering field (preferred)
5+ years of overall experience in developing, debugging and optimizing high-performance sparse linear algebra software using C++ and parallel programming (ideally using CUDA, MPI, OpenMP, OpenACC, pthreads, or equivalent technologies)
Strong fundamentals in floating point arithmetic and implementation of sparse linear algebra primitives like matrix-vector and matrix-matrix products
Experience in developing, maintaining, and testing sparse linear algebra libraries
Strong collaboration, communication, and documentation habits

Responsibilities

Designing, implementing and optimizing scalable high-performance numerical sparse linear algebra software for existing and future GPU architectures
Working with library engineers, QA engineers, and interns on topics ranging from sparse BLAS operations to advanced direct and iterative sparse solvers
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

Skills

Key technologies and capabilities for this role

cuSPARSEcuDSSSparse BLASSparse Linear AlgebraGPU KernelsCUDAC++Sparse SolversIterative SolversPreconditionersAlgebraic MultigridHigh-Performance ComputingNumerical Algorithms

Questions & Answers

Common questions about this position

What education and experience are required for this role?

A PhD or MSc degree (or equivalent experience) in Computational Science and Engineering, Computer Science, Applied Mathematics, or related field is preferred, along with 5+ years of experience in developing, debugging, and optimizing high-performance sparse linear algebra software using C++ and parallel programming.

What key skills are needed for the Senior Math Libraries Engineer position?

Candidates need strong fundamentals in floating point arithmetic and implementation of sparse linear algebra primitives like matrix-vector and matrix-matrix products, experience with C++ and parallel programming technologies such as CUDA, MPI, OpenMP, and strong collaboration, communication, and documentation habits.

What does the day-to-day work involve in this role?

You will design, implement, and optimize scalable high-performance numerical sparse linear algebra software for GPU architectures, work with library engineers, QA, and interns on sparse operations and solvers, and collaborate with product management on feature requirements and roadmaps.

What makes a candidate stand out for this position?

Stand out with good knowledge of CPU and/or GPU hardware architecture and low-level GPU performance optimization, familiarity with multi-frontal factorizations, iterative solvers, preconditioners, and algebraic multigrid, plus experience adopting and advancing software development practices.

Is this a remote position or does it require working in an office?

This information is not specified in the job description.

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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