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etched

Infrastructure Engineer - Labs

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About Etched

Etched is building hardware for frontier intelligence. We co-design chips, racks, software, and manufacturing to deliver best-in-class throughput and latency across both prefill and decode workloads. Our first products are heavily focused on inference . Backed by hundreds of millions from top-tier investors and staffed by leading engineers, Etched is redefining the infrastructure layer for the fastest growing industry in history.

Job Summary

Every Etched system starts its life in a lab. Before a rack-scale inference product reaches a customer, it goes through bring-up, validation, and testing in our factories, labs, or data centers, and each of those environments needs networked, provisioned, monitored infrastructure that is ready before the hardware arrives. The Infra Labs team builds and runs that infrastructure.

As an Infrastructure Engineer on Infra Labs, you will own the racks and server infrastructure across Etched's labs and data center sites, from our office lab at Santana Row to our new hardware facility in Milpitas and our Bay Area colocation footprint. Once our forward-deployed engineers physically install a system, you take it from there: getting it onto the network, provisioned, connected to the storage and compute services it depends on, observable, and healthy through bring-up and testing. You'll support our current rack-scale systems, stand up labs for our next-generation racks and next-generation silicon, and help build the internal deployments that let us run our systems the way our customers do.

This is not a cloud role, and it is not a production SRE role. It is hands-on, full-stack infrastructure delivery in environments that change every week. One week you might rebuild a network-boot provisioning flow for a new server type, chase a NIC firmware or PCIe issue on a liquid-cooled development kit, and rack and cable a new lab row. You'll work alongside Lab Operations, Supercomputing, and Deployment teams to figure out what needs to be built, and then build it with scale in mind from day one: we are designing for gigawatt-scale inference deployments, not a handful of racks.

Key Responsibilities

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