About the role#
The Sparse Linear Algebra team develops libraries like cuSPARSE, which serve as foundational components for high-performance computing and deep learning software stacks. These libraries provide computing primitives for operations such as sparse matrix-vector and sparse matrix-matrix products. You will work with senior software engineers to develop and optimize algorithms that support fields ranging from machine learning to autonomous driving and chip modeling.
What you'll do#
- Prototype and develop numerical algorithms for high-performance sparse linear algebra libraries on GPUs.
- Analyze the performance of GPU implementations to identify opportunities for improvement.
- Collaborate with team members to define APIs and understand software requirements.
- Implement new numerical algorithms and find solutions for difficult numerical corner cases.
What you'll need#
- Currently pursuing an MS or PhD in Computational Science, Computer Science, Applied Mathematics, or a related program.
- Strong skills in C++ programming, debugging, performance analysis, and test design.
- Experience implementing sparse linear algebra algorithms.
- Parallel programming experience using CUDA or OpenMP.
- Experience with domain-specific language design, code and kernel generation, and compiler optimizations.
- Exposure to numerical methods, floating-point arithmetic, and numerical error analysis is a plus.
- Familiarity with GPU or CPU hardware architecture, Python, and sparse compilers like MLIR or TACO is helpful.
Location & details#
- Location: Santa Clara, California.
- Term: Summer 2027.
- Status: Full-time, paid internship.
- Hourly rate: 20 USD to 71 USD.
- Applications are accepted until October 17, 2026.
About NVIDIA
NVIDIA operates as a computer hardware manufacturer based in Santa Clara, California. Founded in 1993, the company focuses on accelerated computing and graphics technology. It produces hardware for markets including artificial intelligence, gaming, and data centers. The organization employs over 50,000 people and maintains a global presence.
How to get in at NVIDIA
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