PhD Research Intern, System Software and I/O Architecture - Fall 2026

NVIDIA•Champaign, CA

15d

About The Position

NVIDIA is seeking a Research Intern with a focus in System Software and System I/O Architecture to contribute to the development of future fast, scalable storage accesses by GPU threads. Scalable systems in a post-Moore world require co-optimization of architecture, runtime systems, operating systems, and compilers, to achieve high throughput while improving energy efficiency. We are seeking candidates with a proven track record of research excellence, systems-building experience, a broad perspective across the field of system software, inference and database GPU systems, depth in I/O system software, I/O systems architectures, deep knowledge in GPU architecture, proficiency in CUDA programming, programming large-scale clusters, and experience in profiling and system performance analysis tools. NVIDIA has pioneered programmable GPUs and the CUDA language, and is a world leader in high-performance and AI computing technology, with ambitious plans for future processors. This position offers you the opportunity to have a real impact in a multifaceted, technology-focused company.

Requirements

Currently pursuing a Ph.D. in CE/CS/EE or similar program area.
Research experience in computer architecture, operating systems, system administration, compilers, and/or HPC.
Research experience designing and optimizing accelerated computing applications, with expertise in areas such as LLM inference, GPU-native database engines, and vector similarity search algorithms.
Demonstrated expertise in one specific area of the above topics with the ability to become the go-to resource within a team from differing backgrounds.
Experience with experimental computer architecture research, software infrastructure development and evaluation.
A track record of well-documented open-source software release.
Ability to work with emerging workloads such as recommender systems, graph analytics, and data frames.

Nice To Haves

Experience with C, C++, CUDA, Python, Rust, and scripting languages.
MPI and NCCL would be a plus.
Strong interpersonal skills and being a creative and dynamic presenter is a huge advantage.
A strong publication, patent, presentation, and research collaboration history is highly valuable.

Responsibilities

Develop novel architectures and system software implementations to enable scalable multi-GPU platforms.
Understand and analyze the interplay between application, operating systems, CPU and GPU architectures, and efficient algorithm designs.
Collaborate with a diverse set of teams across the company, spanning software research, hardware engineering, and product groups.
Publish original research and speak at conferences and events.