Network Engineer

Network Engineer

Location: San Francisco, CA / Remote (US) · Full-Time · Travel up to 25%

About the company

The company is a market and infrastructure platform to buy, sell, and operate compute.

We believe demand for compute will grow exponentially. So fast that a handful of vertically integrated providers won't be able to scale across operations, capital, supply chains, and politics to serve it. The result is a massive wave of fragmentation, with AI factories of every shape and size coming to market to fill this demand. Our job is to enable all of that fragmented compute to flow through one platform, delivering reliable capacity to model builders, research labs, and inference providers when they need it.

We believe every spare electron should be made productive for AI and we're building the platform that makes that possible.

We sit at the center of three forces

• Companies that need reliable, high-performance compute fast

• A fragmented global supply of GPUs across hyperscalers, neoclouds, and independent data centers

• Capital, risk, and operational complexity that most teams are not equipped to manage

When we succeed, trillions of dollars of compute will flow through the company. Builders get capacity when they need it. Providers get a reliable way to monetize, operate, and finance infrastructure at scale. Capital gets an easy way to deploy, hedge, and underwrite. In five years, the company won't just participate in the AI infrastructure market. We will shape it.

The Role

The company's infrastructure team designs, deploys, and operates large-scale GPU clusters for AI labs and compute providers. The Network Engineer designs and brings up the networks in our GPU clusters: compute fabric, storage network, front-end, and out-of-band management. You work with the Cluster Architect on design and with deployment engineers on site through validation. You report to the Head of Infrastructure.

What You'll Own

• Compute fabric: InfiniBand (NDR, XDR) and Spectrum-X Ethernet fabrics, including rail-optimized topologies and NVLink domain integration.

• Storage and front-end networks: Design and capacity planning for storage traffic, tenant access, and internet and cloud interconnect.

• Cabling and optics: Cabling plans, optics BOMs, and labeling standards integrators can build from.

• Bring-up and validation: Fabric bring-up, NCCL and fabric performance testing, and sign-off for acceptance.

• Troubleshooting: Escalation point for fabric issues during deployment and in Day 2.

• Automation: Configuration templates and tooling so each build starts from a known-good baseline.

What We're Looking For

• GPU fabrics at scale: Hands-on design and bring-up of InfiniBand or RoCE fabrics for clusters of 1,000+ GPUs.

• Tooling: Experience with NVIDIA UFM and switch operating systems such as Cumulus or SONiC.

• Physical layer: Practical knowledge of optics, transceivers, and high-density cabling.

• Automation: Python and Ansible or similar for configuration and validation.

Strong Candidates May Have

• NVL72: Experience with GB200 or GB300 NVL72 rack-scale systems.

• Multi-site: Data center interconnect and cloud interconnect design.

• Customer-facing: Experience working directly with customer ML infrastructure teams.

Why You'll Love It Here

• Own the network design standard for our clusters

• Work on current and next-generation fabrics across many sites and customers

• High talent density, high trust team shaping the compute market

• Comprehensive benefits for you and your dependents, including healthcare, dental, and vision coverage, 401(k), and unlimited PTO

The company Cluster is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.