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 @ 2
Algorithms
CUDA
Communication @ 3
GPU
HPC
Mathematics @ 3
Networking @ 3
Parallel Programming @ 3
Python @ 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 Research is seeking networking innovators to join the NVResearch team. As a research intern, you will contribute to the development of future high-performance networking and computing systems. The role requires a background in systems research and an understanding of computer architecture and communication systems for distributed computation. NVIDIA's Research team works with programmable GPUs and CUDA to develop new technologies and inventions.
Responsibilities
- Develop algorithms and design hardware and software extending the state of the art in computing, networking, and related technology areas.
- Invent new techniques, technologies, methodologies, processes, and devices to enable new products or product types.
- Deliver research results including prototypes, patents, and publications.
- Contribute to research informing NVIDIA's technology direction 5–10 years into the future, focusing on long-horizon problems rather than currently shipping products.
- Optimize communication stacks for AI training and inference.
- Design network protocols and congestion-control mechanisms.
- Co-design AI systems across software and hardware.
- Develop circuits and microarchitecture for network controllers and switches.
- Architect networks based on optical switching and silicon photonics.
Requirements
- Pursuing a PhD in Computer Science, Computer Engineering, Electrical Engineering, Physics, Mathematics, or an equivalent program.
- Relevant industry or university research experience in hardware, software, or networking.
- Background in networking architectures, topologies, routing, and system design.
- Publications at top-tier conferences such as ISCA, HPCA, NSDI, or SIGCOMM, or research clearly on track toward publication at such venues.
- Hands-on experience simulating networks and high-performance computing systems.
- Familiarity with inference and training systems for AI models and their associated communication patterns.
- Excellent programming skills in a rapid prototyping environment such as Python, as well as C++ and parallel programming.
- Experience building or using AI agents to accelerate research by automating experiments, analyzing results, or generating and reviewing code.
Benefits
- Eligible for NVIDIA intern benefits.
- NVIDIA is committed to fostering an inclusive work environment and is an equal opportunity employer.
Applications will be accepted at least until September 25, 2026. This posting is for an existing vacancy. NVIDIA uses AI tools in its recruiting processes.
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