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SkyPilot accelerates AI compute across clusters, turning fragmented resources into a single optimized pool. We are seeking a Forward Deployed Engineer to embed with customers end-to-end, deploying SkyPilot in their clouds, Kubernetes clusters, and data centers.
You’ll map workflows to SkyPilot, drive production deployments, and solve hard problems that keep customers from production readiness. You’ll own the technical success, partnering with frontier AI teams and guiding engineers and leaders
SkyPilot accelerates the world's most ambitious AI teams. SkyPilot turns fragmented AI compute across clusters into one optimized, highly available and easy-to-use pool: a single AI supercomputer.
SkyPilot (10k+ GitHub stars, 18M+ downloads) manages the GPU fleets of 100s of companies, from Fortune 500s to top AI-natives like Abridge, Applied Compute, Mistral, Unconventional AI, H Company, and Nubank, with usage growing exponentially. Born in the UC Berkeley lab behind Spark and Databricks, our growing team includes top-tier talent from Databricks, Google, Berkeley, MIT, CMU, and Cornell. To date, SkyPilot has raised over $20M in seed funding from top investors (incl. Lux, Coatue, Amplify) and operators (incl. Ali Ghodsi, Jeff Dean, Guillermo Rauch, Amjad Masad, Clem Delangue, Aaron Levie).
SkyPilot powers frontier AI teams and enterprises that run our platform inside their own clouds, Kubernetes clusters, and data centers. We're looking for a Forward Deployed Engineer to embed with them end to end — deploying and integrating SkyPilot, shaping how their workflows map onto it (and how SkyPilot adapts to them), and solving the hard problems that stand between a customer and production. You'll own the technical side of making customers wildly successful. You're the person a frontier team leans on to get SkyPilot running in their own infrastructure.
Location: San Mateo, CA. Remote will be considered for exceptional candidates.