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AI Idle GPU Detection and Reclamation Engineer

Xivio Solutions

Hybrid · $100k – $130k / year · Contract-to-hire · Posted 3 months ago

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About the role

Our infrastructure bill grew faster than our GPU utilization did last quarter, and finance wants an answer before next quarter's budget review — that answer is idle capacity nobody's tracking closely enough. You'll build the detection system that identifies GPUs sitting idle or under-utilized across our Kubernetes clusters, and the reclamation logic that safely returns that capacity to the scheduling pool without disrupting jobs that only look idle because they're between processing steps. This starts as a contract engagement with a clear path to full-time, splitting time between remote work and our office for infrastructure planning syncs.

Responsibilities

  • Build detection for idle or under-utilized GPUs across Kubernetes clusters
  • Design safe reclamation logic that avoids disrupting legitimately paused jobs
  • Integrate reclaimed capacity back into the scheduling pool
  • Report utilization improvements to finance and infrastructure leadership
  • Participate in on-site infrastructure planning syncs

Requirements

  • Strong Kubernetes and Docker experience with GPU workloads
  • AWS infrastructure experience at scale
  • Experience distinguishing genuinely idle resources from paused-but-active jobs
  • Contract-to-hire availability preferred
  • Comfort working under budget-driven urgency

Benefits

  • Hybrid role with path to full-time conversion
  • Health insurance during contract period
  • 401k matching upon conversion
  • Flexible remote work otherwise
  • Direct visibility into infrastructure cost savings

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Categories

MLOps & AI Infrastructure

Skills

python kubernetes docker aws

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Level

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Language

English

Salary Range

$100k – $130k / year

AI Expertise

MLOps & AI Infrastructure

Skills

python kubernetes docker aws

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