PhD Research Intern, System Software and I/O Architecture - Fall 2026
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Key details
Job Description
We are now looking for a PhD Research Intern with a focus in System Software and I/O Architecture!
NVIDIA is seeking 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.
What you'll be doing:
- 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.
What we need to see:
- 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.
Ways to stand out from the crowd:
- 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.
NVIDIA is widely considered to be one of the technology world's most desirable employers. We have some of the most forward-thinking and productive people in the world working for us. If you're creative and collaborative researcher, we want to hear from you!
Our internship hourly rates are a standard pay based on the position, your location, year in school, degree, and experience. The hourly rate for our interns is 30 USD - 94 USD.
You will also be eligible for Intern benefits.
Applications for this job will be accepted at least until June 28, 2026.This posting is for an existing vacancy.
NVIDIA uses AI tools in its recruiting processes.
NVIDIA is committed to fostering an inclusive work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.#deeplearningAudit details(provenance, verification trail, raw fields)
Core fields
nvidia:JR2019667Provenance
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