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.
Algorithms @ 3
CUDA @ 6
GPU @ 6
HPC @ 3
LLM @ 3
Performance Analysis @ 6
Profiling @ 6
System Administration @ 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
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.
This position offers you the opportunity to have a real impact in a multifaceted, technology-focused company.
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.
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.
Benefits
You will also be eligible for Intern benefits.