PhD Software Engineering Intern, Decision Intelligence - Fall 2026

at Nvidia

📍 Santa Clara, United States

USD 30-94 per hour

INTERN

✅ On-site

Tech Stack
Tag name is followed by "@" symbol and proficiency level value. About proficiency levels:

1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;

3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;

7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;

10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.

AI Algorithms @ 6 CUDA @ 2 GPU @ 3 Machine Learning Performance Optimization @ 3 Python @ 5 System Architecture @ 3

Details

NVIDIA is tapping into the unlimited potential of AI to define the next era of computing. The cuOpt team is redefining decision-making systems with a GPU-accelerated open-source platform, and you can help build the future of decision intelligence.

Responsibilities

Prototype and develop parallel algorithms for decision optimization problems
Performance tuning, optimization, and benchmarking of large-scale parallel numerical software
Collaborate with team members to understand software use cases and requirements

Requirements

Pursuing a PhD degree in Computer Science or a related field
Excellent parallel C++ programming, with familiarity in CUDA programming
Deep understanding of algorithms and numerical methods fundamentals in operations research and optimization
Mathematical programming (linear, quadratic, mixed-integer) and/or fundamentals of heuristics like genetic algorithms and large neighborhood search
Ability to work independently and lead your own development effort

Ways to stand out from the crowd

Experience in algorithmic discovery via autoresearch agents and automated code evolution
Track record of relevant open-source contributions in optimization, machine learning, or GPU programming
Understanding of hardware and system architecture, including CPU/GPU/Memory/Storage, and everything related to performance optimization
Proficiency in a scripting language, preferably Python

Applications for this job will be accepted at least until May 26, 2026.