Product Quality Engineer

Meta Meta · Big Tech · Fremont, CA

This role is for a Product Quality Engineer on Meta's Hardware Engineering team, focusing on the manufacturing readiness and quality of next-generation AI/ML hardware, including compute and GPU platforms, from concept to mass production. The role involves driving manufacturing metrics, developing and validating test requirements, debugging hardware issues, and ensuring quality and reliability at hyperscale volumes.

What you'd actually do

  1. Drive manufacturing metrics (yield, throughput, cycle time, first-pass yield rate) across NPI and MP phases, tracking progress against established targets and escalating risks proactively
  2. Develop, validate, and implement manufacturing and test requirements for advanced compute and GPU systems from NPI through to mass production (MP)
  3. Evaluate and enhance test coverage, methodologies, and infrastructure to improve hardware reliability and performance at scale against defined targets
  4. Drive hardware debugging efforts, contributing to the Major Issue List and executing root cause analysis and Failure Analysis and Corrective Actions (FACA) to resolve hardware issues and meet yield targets
  5. Travel internationally to supplier sites (up to 25%) to manage hardware validation, ensure compliance with test requirements, and maintain technical partnerships

Skills

Required

  • 6+ years of experience in manufacturing engineering or a related field
  • Experience in program and project management, supporting complex hardware products from NPI through to high-volume mass production (MP) launch
  • Working knowledge of hardware architecture with hands-on experience in the testing and validation of compute and GPU systems
  • Background in process development, bring-up, and qualification, encompassing final assembly, test, and packout processes
  • Experience partnering with stakeholder teams to drive alignment on technical decisions, through proposals, design reviews, or presentations
  • Scripting of test cases for compute / storage / AI/ML servers and racks
  • Experience working with international contract manufacturers
  • Experience working within quality management systems such as ISO 9001 or in a hardware manufacturing environment
  • Experience with data center hardware manufacturing at hyperscale
  • Experience with GPU architectures, high-performance computing systems, or AI/ML infrastructure hardware
  • Experience proactively working on issues that may not be clearly defined
  • Background in reliability engineering methodologies, including accelerated life testing and failure mode analysis
  • Advanced degrees in Electrical Engineering, Mechanical Engineering, Manufacturing Engineering, or a related field
  • Experience with test automation frameworks and manufacturing execution systems (MES)

What the JD emphasized

  • AI/ML hardware
  • compute and GPU platforms
  • hyperscale volumes
  • AI/ML infrastructure hardware