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OpenAI

Manufacturing Quality Engineer – Datacenter Infrastructure

San Francisco$230k–$355kfulltimemidAdded today

About this role

OpenAI seeks an experienced Manufacturing Quality Engineer to establish and manage quality programs for datacenter infrastructure across global manufacturing partners. This role oversees vendor audits, performance metrics, and process improvements to ensure reliable, on-time delivery of critical datacenter systems while requiring 40–60% travel.

What you'll do

  • Conduct vendor audits and performance evaluations across production, inspection, testing, and delivery phases
  • Develop and track quality metrics to identify trends and assess manufacturing performance
  • Partner with vendors to refine processes, training, and quality controls to mitigate risks
  • Lead corrective and preventive action plans for audit findings and nonconformances
  • Facilitate root cause analysis for manufacturing issues and drive systemic improvements
  • Monitor manufacturing schedules and ensure testing documentation aligns with project milestones

What they're looking for

  • Manufacturing quality management and supplier quality engineering
  • Data analysis and process improvement methodologies
  • Vendor audit and performance management
  • Datacenter infrastructure systems (mechanical, electrical, controls)
  • Cross-functional communication and stakeholder influence
  • Root cause analysis and corrective action planning
  • Quality systems compliance and documentation
  • Project schedule and milestone tracking
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OpenAI

OpenAI builds AI infrastructure and products, including large-scale data center campuses for AI computing and generative AI applications for enterprise customers. The company is hiring civil engineers, project engineers, electrical design engineers, data center R&D engineers, and AI deployment engineers to expand its infrastructure capabilities and help customers deploy AI solutions.

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Likely interview questions

  • Walk us through your experience managing supplier quality programs for mission-critical or complex projects—what metrics did you track?
  • How have you approached vendor audits and corrective action planning when you identified systemic manufacturing issues?