Reliability Engineer

Intel•Us, MA

7d•Onsite

About The Position

Join us to help build the next generation of AI hardware solutions. You will be part of a highly skilled, agile team developing cutting-edge hardware for the AI domain, where we push the boundaries of what silicon can do for emerging AI workloads. With a startup-like culture, we move quickly and give engineers the opportunity to drive significant technical and business impact. We are continuously developing modern and effective working methods, including hands-on adoption of AI tools throughout the chip development flow.

Requirements

BS/MS/PhD in EE/ME Reliability or related; and/or at least 4-6 yrs experience.
Experience authoring and owning reliability specs and requirement flow-down.
Strong RAS, FMEA, statistical reliability (Weibull, FIT) skills.
Experience with large-scale fleet telemetry and thermal/power redundancy.

Nice To Haves

AI cluster operations, data analytics (Python/SQL).

Responsibilities

Define and own the pod-level reliability specifications that ensure the availability, resilience, and serviceability of a large-scale data center across hardware, thermal, and operational dimensions.
Define and maintain pod-level reliability/availability specs and targets (MTBF, AFR, RAS) for compute, memory, storage, network, power, and cooling subsystems.
Translate system/SLA requirements into pod and subsystem level reliability specs; flow requirements down to silicon, platform, and facilities teams.
Lead FMEA, root-cause analysis, and pod fleet failure-data analytics to drive corrective actions and spec updates.
Architect RAS features (ECC, memory mirroring, predictive failure, telemetry) and graceful degradation/redundancy against pod-level specs.
Partner with facilities on pod power/cooling redundancy (N+1, 2N), thermal margins, and disaster-recovery readiness.
Establish HALT/HASS, burn-in, qualification processes; track field returns and KPIs against pod spec.