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# software engineering interns

- **Company:** Nvidia International, Inc.
- **Location:** Santa Clara, United States
- **Salary:** $41,600.0 - $195,520.0
- **Contract:** Internship / Graduate position
- **Skills:** Application Programming Interfaces (APIs), C++ (Programming Language), Nvidia CUDA, Software Debugging, Python (Programming Language), OpenCL, Software Engineering, Gpu Programming, Gaussian, Information Technology
- **Published:** November 4, 2026
- **Apply:** https://startup.jobs/math-libraries-intern-cuest-summer-2027-2100-nvidia-usa-10665048

## About the Role

* Pursuing a BS, MS, or PhD degree in Computational Chemistry, Computational Physics, Computer Science, Applied Math, or an equivalent program area.
 * Excellent C/C++ or Python programming, debugging, performance analysis, and test design skills.
 * Strong algorithms and numerical methods fundamentals.
 * Ability to work independently and lead your own development effort.
 * Good teamwork, communication, and documentation habits.

Ways to stand out from the crowd:

 * GPU programming experience (CUDA or OpenCL) is desired but not required.
 * Coursework or research experience in quantum chemistry or electronic structure theory is desired but not required.
 * Knowledge of floating-point arithmetic and numerical error analysis.
 * Knowledge of CPU or GPU hardware architecture.
 * Experience using agentic AI tools to improve the speed and quality of software development.

## Description

During your internship, you will work with senior engineers on the cuEST team who will mentor you and guide you in developing highly optimized algorithms and numerical methods for quantum chemistry. Projects may involve implementing new quantum chemistry primitives, defining APIs, analyzing and improving GPU performance, finding solutions for difficult numerical corner cases, and other software engineering work that goes into shipping a production CUDA-X library.

What you'll be doing:

 * Prototype and develop GPU-accelerated algorithms for Gaussian-basis quantum chemistry primitives in cuEST.
 * Analyze the performance of CUDA implementations, identify opportunities for improvement, and implement them.
 * Contribute across the engineering lifecycle, from design and testing to code that ships in the library.
 * Collaborate with team members and other stakeholders to understand how quantum chemistry applications use cuEST and what they need from it.