Lead a team of systems engineers building and operating a GPU compute platform for frontier-scale AI training runs across multiple cloud providers. Own fleet reliability, multi-cloud scheduling, architecture decisions, vendor management, and stay hands-on with code. Requires deep systems engineering experience, strong coding ability, and expertise in orchestration, storage, or GPU hardware.
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Job Description
An extremely well-funded and innovative AI research lab training frontier-scale foundation models is seeking a Compute Platform Lead. This person will own the GPU compute layer that its largest training runs depend on.
The team runs a Kubernetes-based platform across several GPU cloud providers. That makes for hard systems problems: scheduling across multiple clouds, node health, and debugging performance at scale. You will lead the team that builds and runs this layer, and you will stay hands-on enough to ship code yourself.
What you will do
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