Data Center Hardware Quality & Reliability Engineer

Job summary

Responsibilities

Own the end-to-end data-center hardware quality and reliability loop for OpenAI’s 3P infrastructure and 1P current and next-gen platforms. Turn field failures into quantified risk, fast containment, verified root cause, improved MQE/NPI and manufacturing-test coverage, accurate spares forecasts…

• Build and govern the field-quality data model across telemetry, tickets, RMA/repair, FA, firmware, configuration, supplier, and manufacturing genealogy.
• Define AFR, ASR, DPPM, MTBF/MTTR, repeat-repair, NTF, repair-cycle-time, and forecast-versus-actual metrics with explicit denominators and uncertainty.
• Provide fleet-level macro views and unit/FRU/cohort-level micro views; detect shifts and bound affected populations.
• Lead systemic field-failure triage, containment, failure analysis, 8D/CAPA, risk assessment, corrective-action verification, and recurrence monitoring.
• Develop cohort, life-data, reliability-growth, and spare-demand projections by product, FRU, supplier, configuration, geography, and age.

What they're looking for

• BS in electrical, mechanical, computer, materials, reliability engineering, physics, or equivalent experience; MS preferred.
• 8+ years in hardware quality/reliability, server/rack systems, or mission-critical infrastructure; 3+ years owning field-failure, RMA, or CAPA outcomes.
• Solid working understanding of hardware and system architecture across board, tray, rack, firmware, telemetry, manufacturing test, and fleet behavior; deep expertise in every…
• Reliability statistics: censored life data, Weibull/Poisson/binomial methods, confidence bounds, MTBF/MTTR, and reliability growth.
• Hands-on FMEA/FTA, accelerated or reliability-demonstration testing, 8D/CAPA, FA, and corrective-action verification.

Tech stack

• SQL
• Python