Senior Software Engineer - Cluster Networking

NVIDIA; Westford (MA); On-site; USD 184,000 - 357,000; Full time

Benefits offered by this job

Equity

Benefits

Job summary

NVIDIA is seeking a senior networking engineer to lead the network architecture for GPU superclusters. The platform trains across tens of thousands of GPUs on multiple clouds, and we are scaling to clusters of ten thousand nodes and beyond.

You will own Kubernetes networking, design overlay networks and gateways, and build scale-test environments to catch regressions before production. Collaboration across time zones and cloud providers is essential.

Qualifications

• BS/MS in Computer Science, Electrical Engineering or a related field, or equivalent experience.
• 6+ years of professional experience in systems, network or infrastructure software engineering.
• Deep command of Kubernetes networking architecture and CNI standards, with production experience operating Calico strongly preferred.
• Proficiency designing and maintaining modern mesh and VPN networking topologies - Tailscale, WireGuard or equivalent.
• Strong Linux networking fundamentals: routing, netfilter and iptables/nftables, packet marking, network namespaces, and how these interact with container runtimes.
• Demonstrated ability to debug distributed network problems at scale - packet capture, tracing, and correlating behaviour across many hosts to find a single root cause.
• Proficiency in Go, Python, C or a comparable systems language.
• Clear written and verbal communication, and the ability to work effectively with engineers across multiple time zones.

Responsibilities

• Own and evolve the Kubernetes networking architecture for GPU clusters running at multi-thousand-node scale.
• Design, operate and scale the overlay network - CNI, mesh and VPN topologies (Tailscale, WireGuard), and the gateways that connect control and data planes.
• Design, operate and scale the L7 gateways/load balancers/tunnels (Envoy, Cloudflare).
• Find and eliminate scale ceilings: packet loss under load, control-plane saturation, IP address management exhaustion, and the failure modes that only appear above a few thousand nodes.
• Build the scale-test environments and validation suites that let us catch networking regressions before they reach production, rather than during a training run.
• Diagnose hard, ambiguous problems across the stack - where a symptom in Slurm or a training job traces back to a mark collision, a stale route, or a saturated tunnel.
• Partner with cloud and neocloud providers on network topology, requirements and capabilities as we bring up new clusters.
• Provide senior technical judgement to a distributed team, and depth in the Custer Networking domain.

Skills

Kubernetes networking

CNI (Calico)

Linux networking

Go

Python

C

Packet tracing

Education

BS/MS in Computer Science or Electrical Engineering

Tools

Tailscale

WireGuard

Envoy

Cloudflare

Job description

NVIDIA is a pioneer in accelerated computing, known for inventing the GPU and driving breakthroughs in gaming, computer graphics, high-performance computing, and artificial intelligence. Our technology powers everything from generative AI to autonomous systems, and we continue to shape the future of computing through innovation and collaboration. Within this mission, our team, Managed AI Research Superclusters (MARS), builds and scales the infrastructure, platforms, and tools that enable researchers and engineers to develop the next generation of AI/ML systems. By joining us, you’ll help build solutions that power some of the most sophisticated computing workloads globally.

We are looking for a senior networking engineer to lead the network architecture of our GPU superclusters. Our platform runs frontier model training across tens of thousands of GPUs on multiple clouds, and we are scaling it toward clusters of ten thousand nodes and beyond. At that size, networking stops being a configuration exercise and becomes the hardest engineering problem on the platform — and it is currently one of the areas where we most need depth.

What You'll Be Doing

• Own and evolve the Kubernetes networking architecture for GPU clusters running at multi-thousand-node scale
• Design, operate and scale the overlay network - CNI, mesh and VPN topologies (Tailscale, WireGuard), and the gateways that connect control and data planes
• Design, operate and scale the L7 gateways/load balancers/tunnels (Envoy, Cloudflare)
• Find and eliminate scale ceilings: packet loss under load, control-plane saturation, IP address management exhaustion, and the failure modes that only appear above a few thousand nodes
• Build the scale-test environments and validation suites that let us catch networking regressions before they reach production, rather than during a training run
• Diagnose hard, ambiguous problems across the stack - where a symptom in Slurm or a training job traces back to a mark collision, a stale route, or a saturated tunnel
• Partner with cloud and neocloud providers on network topology, requirements and capabilities as we bring up new clusters
• Provide senior technical judgement to a distributed team, and depth in the Custer Networking domain.

What We Need To See

• BS/MS in Computer Science, Electrical Engineering or a related field, or equivalent experience
• 6+ years of professional experience in systems, network or infrastructure software engineering
• Deep command of Kubernetes networking architecture and CNI standards, with production experience operating Calico strongly preferred
• Proficiency designing and maintaining modern mesh and VPN networking topologies - Tailscale, WireGuard or equivalent
• Strong Linux networking fundamentals: routing, netfilter and iptables/nftables, packet marking, network namespaces, and how these interact with container runtimes
• Demonstrated ability to debug distributed network problems at scale - packet capture, tracing, and correlating behaviour across many hosts to find a single root cause
• Proficiency in Go, Python, C or a comparable systems language
• Clear written and verbal communication, and the ability to work effectively with engineers across multiple time zones

Ways To Stand Out From The Crowd

• Direct experience architecting and operating massive-scale Kubernetes topologies across thousands of concurrent nodes
• Experience with high-performance fabrics in AI or HPC environments - InfiniBand, RoCE, or RDMA over converged networks
• Upstream contributions to Calico, Cilium, Tailscale, or Kubernetes networking SIGs
• Experience operating networking across multiple public clouds and on-premises environments simultaneously
• Familiarity with Slurm or other HPC schedulers running on Kubernetes

Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 184,000 USD - 287,500 USD for Level 4, and 224,000 USD - 356,500 USD for Level 5.

You will also be eligible for equity and benefits.

Applications for this job will be accepted at least until September 19, 2026.

This posting is for an existing vacancy.

NVIDIA uses AI tools in its recruiting processes.

NVIDIA is committed to fostering an inclusive 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.