Andromeda

Andromeda

Member of the Technical Staff - Platform

North America Remote / San Francisco, CA · Staff+ · Full-time

Sponsorship not specifiedDetected 1 day ago
PostgreSQLCloud PlatformsKubernetesCI/CDLinux

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odds of building a lasting career here

25Risky
Cap-exempt (no lottery)0
Sponsors this role35
Entry-level history0
PERM / green-card track0
Lottery odds40
Fits your clock70

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About the role

  • The automated systems that take a cluster from bare machines to customer-ready
  • Operating Kubernetes and Postgres across the fleet
  • Contributing to our custom Kubernetes operators

Requirements

  • Impressive technical work you can go deep on, with impact in the world.
  • 2+ years of on-call experience for critical production services
  • Experience operating databases, monitoring, CI/CD, and cloud infrastructure at scale
  • Familiarity with fleet management and capacity planning

Nice to have

  • Prior experience writing operators, or with GPUs, HPC scheduling, or bare-metal hardware is nice to have, but not required.

Company info

  • Compute is the most sought-after resource in the world, yet it still trades like commercial real estate: year-long contracts, manual fulfillment, capacity sitting idle because nobody can move it.
  • We are building the liquidity layer at Andromeda.
  • Andromeda was founded by Nat Friedman and Daniel Gross to give startups the scaled AI infrastructure once reserved for hyperscalers.
  • The first cluster filled almost instantly.
  • The years since went into the platform that makes compute liquid:
  • it deploys into foreign datacenters and turns the hardware it finds into clusters that leading AI labs train on.
  • Today Andromeda operates compute for 80+ customers across 30+ capacity providers, with tens of thousands of GPUs under management and billions of GPU-hours supported, on everything from A100 to GB300.
  • We are looking for engineers to build and operate the control plane that runs our fleet.

This listing is sourced directly from Andromeda's careers page and normalized into a canonical job model.