Principal Software Engineer - Networking Hyperscale Engineering

Principal Software Engineer – Networking Hyperscale Engineering

NVIDIA is looking for an experienced Principal Software Engineer to join the US-based Networking Hyperscale Engineering Team. You will work directly with top‑tier cloud and AI customers to co‑develop software that powers AI superclusters, influencing NVIDIA’s NIC software roadmap across the Linux kernel, RDMA/RoCE, DPDK, DOCA, NCCL, and NIC firmware.

• Co‑develop NIC software and communication paths with strategic customers to enable and scale large AI superclusters.
• Design and implement high‑performance C/C++ components on Linux using DPDK, kernel‑bypass techniques, and RDMA/RoCE.
• Develop and integrate kernel, driver, and NIC firmware features to improve throughput, latency, and reliability for AI workloads.
• Collaborate with NCCL and distributed training teams to tune end‑to‑end collectives performance over NVIDIA networking at scale.
• Own complex performance and functionality debugging with customers and represent the team in cross‑org architecture discussions.

• 15+ years of experience in systems or networking software roles.
• Bachelor’s, Master’s, or PhD in Software Engineering, Computer Science, Computer Engineering, Electrical Engineering, or equivalent experience.
• Deep expertise in C/C++, strong Linux systems knowledge, and hands‑on experience with kernel networking / RDMA / NIC drivers or DPDK.
• Proven experience developing and debugging network operating systems and routing/switching protocols used in AI data centers (e.g., BGP, ECMP, EVPN/VXLAN).
• Practical experience with DOCA, NIC firmware interfaces, or other hardware‑accelerated networking stacks for large‑scale systems.
• Excellent communication skills and a track record of effective collaboration with developers, partners, and customers in dynamic environments.

• Deep knowledge of Linux kernel and systems internals, SoC/Smart
  
  NIC/NIC embedded systems, and data‑center switches and NOS.
• Hands‑on experience with RDMA/RoCE, GPU‑related networking (e.g., GPUDirect RDMA), and high‑performance, low‑latency data paths.
• Background optimizing NCCL or other distributed training stacks on large GPU clusters for throughput and tail latency.
• Experience working with hyperscalers or major cloud providers on performance‑critical AI networking deployments.
• Contributions to open‑source networking, RDMA, DPDK, kernel, CUDA/NCCL, or related ecosystems.

Base salary range: 248,000 USD – 391,000 USD, based on location, experience, and peer compensation.

Eligible for equity and benefits.

Applications accepted until May 19, 2026.

NVIDIA is committed to fostering a diverse work environment and is an equal‑opportunity employer. NVIDIA does not discriminate 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.