We are looking for software engineers to join our development efforts in the area of sparse linear algebra kernels for high-performance libraries such as cuSPARSE and cuDSS. 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, 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 basic sparse BLAS operations like matrix-vector-products and matrix-matrix-products, direct sparse solvers, iterative sparse solvers, preconditioners, and algebraic multigrid (AMG). 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 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
What we need to see:
PhD or MSc degree (or equivalent experience) in Computational Science and Engineering, Computer Science, Applied Mathematics, or related science or engineering field is 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.
Ways to stand out from the crowd:
Good knowledge of CPU and/or GPU hardware architecture and low-level GPU performance optimization
Familiarity with technologies such as multi-frontal factorizations, iterative solvers, preconditioners, and algebraic multigrid
Experience with adopting and advancing software development practices such as CI/CD systems and project management tools such as JIRA
Understanding of large-scale computing technologies such as PDE solvers, eigenvalue solvers and time-domain simulation methods (e.g., CFD, FEA)
Working experience in a globally distributed and agile organization
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.
NVIDIA is widely considered to be one of the technology world's most desirable employers. We have some of the most forward-thinking and talented people in the world working for us. If you're creative, autonomous and love a challenge, we want to hear from you!
Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 148,000 USD - 235,750 USD for Level 3, and 184,000 USD - 287,500 USD for Level 4.You will also be eligible for equity and benefits.
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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.”
