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Principal · 12+ years exp
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Confirmed on the employer's own hiring board on Nov 11, 2026. First seen by Alion on Nov 4, 2026. Meta scores B on the Alion truth index.

Overview
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Meta Platforms is an American technology company founded in 2004 as Facebook and renamed in 2021 to signal its investment in immersive computing. It operates the largest family of social and messaging applications in the world, comprising Facebook, Instagram, WhatsApp, Messenger and Threads, and earns almost all of its revenue from advertising sold against that audience. Headquartered in Menlo Park, California, the company also develops the open Llama language models and the Reality Labs division behind Quest headsets and Ray-Ban smart glasses.
Meta is seeking a Product Quality Engineer responsible for developing and implementing robust manufacturing and quality processes for the next generation of disruptive AI hardware products. As the technical owner, you will take primary responsibility for specifying manufacturing and test requirements for Advanced Compute, Accelerator and GPU platforms. You will oversee end-to-end manufacturing readiness for New Product Introduction (NPI), guiding projects from prototype phase through to high-volume Mass Production (MP) launch.

Working closely with external manufacturing partners and internal cross-functional groups like Design Engineering, you will define standards to ensure line readiness, facilitate smooth NPI builds, and enable scalable execution. Furthermore, you will hold responsibility for meeting core manufacturing metrics, conducting failure analysis, and executing corrective actions to maintain top-tier efficiency and quality.

Responsibilities

Lead the development of a comprehensive product quality strategy and process for next-generation AI hardware systems, ensuring timely delivery and defined quality standards Ensure product and process quality targets are met by designing test methods, establishing standards and driving continuous improvement projects with Meta manufacturing partners and key commodity suppliers Spearhead cross-functional troubleshooting across rack and system-level hardware, maintaining ownership of the Major Issue List. Execute rigorous Failure Analysis and Corrective Actions (FACA) to solve underlying technical problems and achieve quality yield goals Early engagement with Meta Engineering teams to implement robust DFx requirements and ensure products meet cycle-time, cost, quality and yield targets Drive the continuous evaluation and advancement of test coverage, methodologies, and infrastructure to maximize hardware reliability, performance, and scalability across the product lifecycle Conduct First Article and Source Inspections reviews on Meta hardware components and assemblies Create BOMs, engineering change notifications, and manufacturing process changes through product lifecycle management tools

Qualifications

BS in Electrical Engineering or equivalent 12+ years of experience in manufacturing and test for Compute, Storage or Network Hardware products Technical understanding of hardware architecture, with proven expertise in defining requirements, testing, and validating high-performance compute and GPU systems Experience collaborating with Original Design Manufacturers (ODMs) to deliver high-quality data center server accelerator products Familiarity with manufacturing test solutions for Data Center Infrastructure hardware products Experience with new product introduction and manufacturing operations Knowledge of quality methodologies and tools Experience applying structured problem-solving methodologies (e.g., root cause analysis, 8D) and communicating technical findings to cross-functional stakeholders Experience adhering to and implementing responsible, ethical AI practices (e.g., risk assessment, bias mitigation, quality and accuracy reviews) Demonstrated ability to integrate AI tools to optimize/redesign workflows and drive measurable impact (e.g., efficiency gains, quality improvements) Scripting skills in Bash, Perl, or Python Demonstrated ongoing AI skill development (e.g., prompt/context engineering, agent orchestration) and staying current with emerging AI technologies Experience working on AI Hardware

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