About the role#
The math libraries team is looking for an intern to help build cuEST, a CUDA-X library that accelerates quantum chemistry on NVIDIA GPUs. You will work with senior engineers to develop highly optimized algorithms and numerical methods. Your work will involve defining APIs, solving numerical corner cases, and contributing to the full engineering lifecycle of a production library.
What you'll do#
- Prototype and develop GPU-accelerated algorithms for Gaussian-basis quantum chemistry primitives.
- Analyze the performance of CUDA implementations and implement improvements.
- Collaborate with team members and stakeholders to understand user needs.
- Contribute to the engineering lifecycle from design and testing to final code.
What you'll need#
- Pursuing a BS, MS, or PhD in Computational Chemistry, Computational Physics, Computer Science, Applied Math, or a related field.
- Excellent C/C++ or Python programming skills.
- Strong fundamentals in algorithms and numerical methods.
- Proficiency in debugging, performance analysis, and test design.
- Ability to work independently and lead your own development effort.
- Good communication, teamwork, and documentation habits.
- Knowledge of floating-point arithmetic, numerical error analysis, and CPU or GPU hardware architecture.
- Experience with agentic AI tools.
- Desired: GPU programming experience (CUDA or OpenCL) and coursework or research in quantum chemistry or electronic structure theory.
Location & details#
- Location: Santa Clara, California.
- Term: Summer 2027.
- Modality: On-site.
- This is a paid, full-time internship position.
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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