Used Tools & Technologies
GenAIRequired Skills & Competences
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.
Python @ 5
Algorithms @ 3
Machine Learning @ 3
Performance Optimization @ 3
System Architecture @ 3
CUDA @ 2
GPU @ 3
Generative AI @ 3
AI @ 3
- 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.
Details
NVIDIA's cuOpt team is building a GPU-accelerated open-source platform for decision intelligence. This internship targets students pursuing a PhD who are passionate about decision optimization, generative AI, and advanced parallel computing techniques. Interns will prototype and optimize parallel algorithms and contribute to large-scale numerical software for decision optimization.
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
- Knowledge of mathematical programming (linear, quadratic, mixed-integer) and/or fundamentals of heuristics such as genetic algorithms and large neighborhood search
- Ability to work independently and lead your own development effort
Ways to stand out / Preferred qualifications
- 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 (CPU/GPU/Memory/Storage) and performance optimization
- Proficiency in a scripting language, preferably Python
Compensation & benefits
- Internship hourly rate: 30 USD - 94 USD
- Intern benefits available: https://www.nvidia.com/en-us/benefits/interns/
Other information
- Applications accepted at least until May 26, 2026
- NVIDIA uses AI tools in its recruiting processes
- NVIDIA is an equal opportunity employer and fosters a diverse work environment.