Networking Systems Software Engineering Intern

NVIDIA

Intern role focusing on AI infrastructure networking and systems software for data-center networking at NVIDIA. Collaborate with teams on performance, reliability, and scalability projects.

Posted 4/29/2026internshipSanta Clara • California, Washington • 🇺🇸 United StatesEntry Level💰 $20 - $71 per hourWebsite

Tech Stack

Tools & technologies

LinuxPythonTCP/IP

About the role

Key responsibilities & impact

Work on AI infrastructure networking and systems software for large-scale data-center networking stacks, focusing on performance, reliability, and scalability.
Develop and optimize software for ConnectX SmartNICs and BlueField DPUs, including drivers, firmware, and DOCA/DPDK-based data-plane applications.
Work on RDMA (RoCE/Ethernet) networking to improve low-latency, high-throughput communication between GPUs, NICs, and DPUs in distributed AI/HPC systems.
Debug and tune end-to-end networking performance in large-scale distributed training environments.

Requirements

What you’ll need

Pursuing a Bachelor’s, Master’s, or PhD program in Computer Science, Computer Engineering, Electrical Engineering, or a related field.
Strong programming skills in C or C++; familiarity with Python or Bash scripting is a plus.
Understanding of networking fundamentals (Ethernet, TCP/IP, RDMA, or RoCE) and experience with Linux development environments.
Solid problem-solving, debugging, and analytical skills.
A genuine passion for AI systems, distributed computing, and high-performance networking.
Prior experience or coursework involving DPDK, DOCA, NCCL, or CUDA.
Hands-on work with embedded systems, NCCL, GPU networking, or data-center scale computing.
Demonstrated self-learning and innovation (hackathons, open-source contributions, side projects).
Strong communication skills and the ability to thrive in collaborative, fast-paced environments.

Benefits

Comp & perks

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Hard Skills & Tools

CC++PythonBash scriptingDPDKDOCANCCLCUDAembedded systemsnetworking performance tuning

Soft Skills

problem-solvingdebugginganalytical skillsself-learninginnovationcommunicationcollaborationadaptabilitypassion for AI systemsability to thrive in fast-paced environments