Senior Math Libraries Engineer - Direct Sparse Solvers

at Nvidia

📍 Santa Clara, United States

USD 184,000-356,500 per year

SENIOR

✅ On-site

Used Tools & Technologies

LLM

Required Skills & Competences
Tag name is followed by "@" symbol and proficiency level value. About proficiency levels:

1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;

3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;

7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;

10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.

Software Development @ 4 CI/CD @ 4 Hiring @ 4 Communication @ 7 Mathematics @ 4 Parallel Programming @ 6 Performance Optimization @ 4 Jira @ 4 Product Management @ 4 Debugging @ 6 Project Management @ 4 QA @ 4 Agile @ 4 CUDA @ 4 GPU @ 4 AI @ 4

Details

We are looking for software engineers to join development of cuDSS, a CUDA library for direct solvers for sparse linear systems. The work supports scientific and engineering simulations, data analytics, and AI using GPUs and high-performance linear algebra libraries across domains such as CAE, EDA, optimization, quantum chemistry, autonomous vehicles, and LLMs. You will help develop GPU-accelerated libraries and SDKs used in those areas.

Responsibilities

Design, implement, and optimize direct sparse solvers for existing and future GPU architectures.
Collaborate with library engineers, QA engineers, and interns across design, implementation, testing, release, and support.
Work closely with product management and internal/external partners to understand feature and performance requirements and contribute to technical roadmaps.
Improve library quality, performance, and maintainability through re-architecting and establishing modern software development practices.

Requirements

PhD or MSc in Computer Science, Computational Science and Engineering, Applied Mathematics, or related field (or equivalent experience).
5+ years of experience developing, debugging, and optimizing high-performance numerical software using C++ and parallel programming.
Experience with CUDA and/or parallel programming technologies such as MPI, OpenMP, OpenACC, pthreads, or equivalents.
Strong fundamentals in floating-point arithmetic and numerical analysis.
Experience implementing sparse linear algebra primitives (e.g., matrix-vector and matrix-matrix products, triangular solves).
Experience developing, maintaining, and testing scientific computing libraries.
Strong collaboration, communication, and documentation habits.

Ways to stand out (Preferred / Nice to have)

Familiarity with direct solver techniques: reordering, multi-frontal and supernodal factorizations, numerical pivoting strategies, iterative refinement.
Knowledge of CPU and/or GPU hardware architecture and low-level GPU performance optimization.
Experience with CI/CD systems, project management tools such as JIRA, and AI agents.
Understanding of large-scale computing technologies such as PDE solvers, eigenvalue solvers and time-domain simulation methods (e.g., CFD, FEA).
Experience working in a globally distributed and agile organization.

Compensation & Benefits

Base salary ranges by level: Level 4: 184,000 USD - 287,500 USD; Level 5: 224,000 USD - 356,500 USD.
Eligible for equity and benefits (link to NVIDIA benefits referenced in posting).

Additional information

Applications accepted until June 13, 2026.
NVIDIA uses AI tools in recruiting processes.
NVIDIA is an equal opportunity employer committed to inclusive hiring practices.