Senior GPU Cluster Networking Architect

NVIDIA; United States; 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 for its Managed AI Research Superclusters (MARS) to lead network architecture of GPU superclusters. The role spans internal/external cluster communication, CNI data plane, and cross-region connectivity across clouds.

You will own Kubernetes networking for multi-thousand-node GPU clusters, design and operate overlay networks, and scale L7 gateways and tunnels using Envoy and related tech. Strong Linux networking and Go/Python/C skills are required.

Qualifications

• BS/MS in Computer Science, Electrical Engineering or 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

• Be the technical owner of how our clusters communicate internally and externally.
• 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, 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 failure modes at thousands of nodes.
• Build scale-test environments and validation suites to catch networking regressions before production.
• Diagnose hard, ambiguous problems across the stack and trace issues across hosts.

Skills

Kubernetes networking

Go

Python

C

Linux networking

Education

BS/MS in CS/EE or equivalent

Tools

Calico

Tailscale

WireGuard

Envoy

Job description

NVIDIA is seeking a senior networking engineer for its Managed AI Research Superclusters (MARS) to lead network architecture of GPU superclusters. The role spans internal/external cluster communication, CNI data plane, and cross-region connectivity across clouds.

You will own Kubernetes networking for multi-thousand-node GPU clusters, design and operate overlay networks, and scale L7 gateways and tunnels using Envoy and related tech. Strong Linux networking and Go/Python/C skills are required.