About this role
Analytical professionals who thrive at the intersection of hardware systems, data analytics, and cross-functional leadership will find this role a strong match. Operating within OpenAI, the team builds and maintains the infrastructure supporting current and next-generation platforms across third-party and first-party environments.
As the first hire in this function, the engineer takes charge of the end-to-end hardware quality and reliability loop. Responsibilities include transforming field failures into quantified risk assessments, executing rapid containment, establishing verified root causes, and driving upstream changes to prevent recurrence. Success requires combining practical hardware knowledge with reliability statistics and the ability to influence design, operations, and suppliers without direct authority.
What you will do
- Build and govern the field-quality data model across telemetry, tickets, repair logs, firmware, configuration, and manufacturing genealogy.
- Define core reliability metrics such as AFR, ASR, DPPM, MTBF, and MTTR with explicit denominators and uncertainty.
- Lead systemic field-failure triage, containment, failure analysis, 8D/CAPA, risk assessment, and corrective-action verification.
- Develop cohort, life-data, reliability-growth, and spare-demand projections by product, FRU, supplier, and configuration.
- Partner with manufacturing quality and NPI teams to convert field mechanisms into test coverage, screening profiles, and design requirements.
- Create concise executive decision packages detailing populations at risk, exposure, confidence levels, recommendations, and costs.
- Run the cross-functional reliability council and mentor future Field Quality Engineers as the team grows.
What you need
- Hold a Bachelor of Science in electrical, mechanical, computer, materials, reliability engineering, physics, or equivalent experience, with a Master of Science preferred.
- Bring 8 or more years of experience in hardware quality, reliability, server or rack systems, or mission-critical infrastructure.
- Possess at least 3 years of direct ownership over field-failure, RMA, or CAPA outcomes.
- Demonstrate a solid working understanding of hardware and system architecture across boards, trays, racks, firmware, telemetry, and manufacturing test.
- Apply reliability statistics including censored life data, Weibull, Poisson, and binomial methods, confidence bounds, and growth modeling.
- Maintain hands-on expertise with FMEA, FTA, accelerated testing, 8D, failure analysis, and corrective-action verification.
- Show working proficiency with SQL and Python, R, or equivalent analytics tools.
Nice to have
- GPU/AI server platforms, liquid cooling, high-power delivery, high-speed networking, rack integration, or data-center operations
- Design for serviceability including FRU boundaries, diagnostics, repair workflows, tooling, and spares policy
- Qualification-to-field correlation and mission-profile development
- ODM, CM, or supplier experience covering failure analysis quality, audits, QBRs, and corrective-action governance
- Linux, BMC, IPMI, Redfish logs, and fleet telemetry
Benefits
- Offers Equity
Skills and tech stack
Questions candidates ask
What is the compensation for this role?
The salary range is $226K to $285K and the position includes offers of equity.
Where is the position located?
The job is based in San Francisco.
What technical skills are needed for the position?
Candidates need working proficiency with SQL and Python, R, or equivalent analytics tools, alongside a solid working understanding of hardware and system architecture.