Data Center Hardware Quality & Reliability Engineer

About The Role 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, and upstream changes that prevent recurrence. The first hire must combine practical hardware/system understanding, reliability engineering, data fluency, and cross-functional technical leadership at data-center scale. Key Responsibilities • 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. • Partner with MQE and NPI to convert field mechanisms into manufacturing-test coverage, screening/stress profiles, diagnostics, control plans, DFR/DFS requirements, FMEA/FTA, mission profiles, FRU strategy, and qualification gates. • Close the loop by verifying whether upstream changes reduce field recurrence. • Define supplier/CM FA standards, field-data contracts, scorecards, escalation paths, and closure evidence. • Provide serviceability, TCO, and spares inputs without owning inventory execution or procurement. • Create concise executive decision packages: population at risk, exposure, confidence, options, cost/risk, and recommendation. • Run the cross-functional reliability council and, as the team grows, mentor the 1P and 3P Field Quality Engineers. Qualifications • 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 subsystem is not required. • 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. • Working proficiency with SQL and Python/R or equivalent analytics tools. • Ability to influence design, validation, operations, suppliers/CMs, and senior leaders without direct authority. Preferred Skills • GPU/AI server platforms, liquid cooling, high-power delivery, high-speed networking, rack integration, or data-center operations. • Design for serviceability: FRU boundaries, diagnostics, repair workflows, tooling/access, and spares policy. • Qualification-to-field correlation and mission-profile development. • ODM/CM/supplier experience: FA quality, audit, QBR, and corrective-action governance. • Linux/BMC/IPMI/Redfish logs and fleet telemetry. • Leadership of a cross-generation reliability program or launch-readiness gate. About OpenAI OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity. We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic. For additional information, please see OpenAI’s Affirmative Action and Equal Employment Opportunity Policy Statement. Background checks for applicants will be administered in accordance with applicable law, and qualified applicants with arrest or conviction records will be considered for employment consistent with those laws, including the San Francisco Fair Chance Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act, for US-based candidates. For unincorporated Los Angeles County workers: we reasonably believe that criminal history may have a direct, adverse and negative relationship with the following job duties, potenti

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 subsystem is not required. 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. Working proficiency with SQL and Python/R or equivalent analytics tools. Ability to influence design, validation, operations, suppliers/CMs, and senior leaders without direct authority.

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. Partner with MQE and NPI to convert field mechanisms into manufacturing-test coverage, screening/stress profiles, diagnostics, control plans, DFR/DFS requirements, FMEA/FTA, mission profiles, FRU strategy, and qualification gates. Close the loop by verifying whether upstream changes reduce field recurrence. Define supplier/CM FA standards, field-data contracts, scorecards, escalation paths, and closure evidence. Provide serviceability, TCO, and spares inputs without owning inventory execution or procurement. Create concise executive decision packages: population at risk, exposure, confidence, options, cost/risk, and recommendation. Run the cross-functional reliability council and, as the team grows, mentor the 1P and 3P Field Quality Engineers.