NVIDIA
Sparse Linear Algebra Libraries Intern - Summer 2027
US, CA, Santa Clara · Internship · Posted Oct 13, 2026
- Education
- Pursuing an MS or PhD in Computational Science, Computer Science, Applied Mathematics, or equivalent program area.
About the job
Develop and optimize GPU-based sparse linear algebra algorithms and libraries for high-performance computing and deep learning.
What you'll do
- Prototype and develop numerical algorithms for GPU sparse linear algebra libraries.
- Analyze GPU implementation performance and identify opportunities for improvement.
- Collaborate with team members to understand software use cases and requirements.
What they ask for
- Pursuing an MS or PhD in Computational Science, Computer Science, Applied Mathematics, or an equivalent program area.
- Strong C++ programming, debugging, performance analysis, and test design skills.
- Experience implementing sparse linear algebra algorithms.
- Parallel programming experience using CUDA and/or OpenMP; experience with domain-specific language design, code/kernel generation, and compiler optimizations.
Nice to have
- Exposure to numerical methods, floating-point arithmetic, and numerical error analysis; knowledge of GPU/CPU and network hardware architecture.
- A scripting language, preferably Python; understanding of compilers and programming languages; familiarity with cuTILE, Tile++, MLIR, or TACO.
Pay
20 USD - 71 USD per hour; hourly intern rate
Tools
C++, CUDA, OpenMP, Python, cuTILE, Tile++, MLIR, TACO
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