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Data Center Infrastructure Architect at OpenAI · San Francisco, CA · Joined
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Data Center Infrastructure Architect

OpenAI · San Francisco, CA · Just now · 0 applicants
NewOn-siteFull-timeLead
Pay
Pay not listed
Workplace
On-site
Job type
Full-time
Level
Lead
Source: jobright · Posted by joined-scrapper

About the role

OpenAI seeks an experienced Data Center Infrastructure Architect to design and optimize physical infrastructure for large-scale AI deployments, spanning electrical and mechanical systems, modeling, telemetry, and implementation. The role focuses on improving efficiency, reliability, cost, and deployment speed while leading technical work in fast-moving environments.

What you’ll do

  • Develop and optimize physical infrastructure for large-scale AI deployments
  • Make system-level design decisions across multiple engineering disciplines
  • Apply simulation, optimization, digital-twin, and physics-based modeling techniques
  • Translate operational telemetry into design improvements
  • Evaluate tradeoffs involving performance, reliability, cost, scalability, and sustainability
  • Lead technical work in ambiguous, rapidly changing environments

What you’ll need

  • Experience designing or optimizing hyperscale data centers or mission-critical facilities
  • Broad knowledge of electrical and mechanical systems including power, cooling, and controls
  • Experience with simulation, optimization, digital-twin, or physics-based modeling
  • Strong understanding of efficiency and performance metrics such as PUE, WUE, and TCO
  • Experience with high-density GPU clusters and direct-to-chip liquid cooling
  • Bachelor's degree in engineering or related technical discipline

Original job description

OpenAI is seeking a senior, hands-on Data Center Infrastructure Architect to develop and optimize physical infrastructure for large-scale AI deployments. The role spans data center architecture, electrical and mechanical systems, computational modeling, telemetry, and implementation, with a focus on improving efficiency, reliability, cost, and deployment…

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