Principal Networking Software Engineer, Hyperscale

NVIDIA is looking for an experienced Principal Software Engineer to expand the US-based Networking Hyperscale Engineering Team. Are you craving an opportunity to work directly with top-tier cloud and AI customers, co-develop software that powers their AI superclusters, and influence NVIDIA’s NIC software roadmap? In this role you will do just that for NVIDIA’s high-performance networking stack spanning Linux kernel, RDMA/RoCE, DPDK, DOCA, NCCL, and NIC firmware.

• Co-developing NIC software and communication paths with strategic, top-tier customers to enable and scale large AI superclusters.
• Designing and implementing high‑performance C/C++ components on Linux using DPDK, kernel-bypass techniques, and RDMA/RoCE.
• Developing and integrating kernel, driver, and NIC firmware features to improve throughput, latency, and reliability for AI workloads.
• Working closely with NCCL and distributed training teams to tune end-to-end collectives performance over NVIDIA networking at scale.
• Owning complex performance and functionality debug with customers and representing the team in cross-org architecture discussions.

• 15+ years overall experience in a similar or related systems / networking software role.
• A Bachelor’s, Master’s or PhD in Software Engineering, Computer Science, Computer Engineering, Electrical Engineering, or a related field (or equivalent experience).
• Deep C/C++ expertise, strong Linux systems knowledge, and hands-on experience with kernel networking / RDMA / NIC drivers or DPDK.
• Proven experience developing and debugging network operating systems (NOS) and routing/switching protocols used in AI data centers (for example 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 / systems internals, SoC / Smart
  
  NIC / NIC embedded systems, and data center switches and NOS.
• Hands-on experience with RDMA/RoCE, GPU-related networking (for example 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 strategic, performance-critical AI networking deployments.
• Contributions to open-source networking, RDMA, DPDK, kernel, CUDA/NCCL, or related ecosystems.

Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 248,000 USD - 391,000 USD. You will also be eligible for equity and benefits.

NVIDIA is committed to fostering a diverse 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.