Software Engineering Intern, Distributed Scientific Computing Libraries - Fall 2025

Job Description

NVIDIA is seeking a software engineering intern to work on CuPyNumeric, a distributed and accelerated replacement for NumPy, to develop GPU-accelerated versions of NumPy and SciPy methods.

Requirements

• Pursuing BS, MS, or PhD degree in Computer Science, Electrical Engineering, or related field
• Strong foundation in modern C++ best practices and object oriented programming
• Experience using Python for numerical computing (e.g. NumPy, SciPy)
• Experience with CUDA C++
• Academic knowledge of tasking or asynchronous runtimes, especially data-centric initiatives such as Legion
• Good written communication, teamwork, and presentation skills

Responsibilities

• Improving performance by developing highly optimized and innovative algorithms for high performance numerical computing
• Architecting, prioritizing, and developing new features in cuPyNumeric and the runtime stack
• Designing future-proof API’s for accelerated numerical/scientific computing libraries
• Contributing to the development of runtime systems that underlay the foundation of multi-GPU computing at NVIDIA
• Writing effective, maintainable, and well-tested code for production use

Benefits

• Multiple relocation packages
• Two weeklong shutdowns (mid-summer and year-end) in the US (in addition to PTO)
• 8-week parental leave
• 9 Employee Resource Groups
• Annual bonus offering
• Flexible work arrangements
• Up to 6% 401K matching