Product Quality Engineer

Responsibilities

• Own and drive key manufacturing metrics including yield, throughput, cycle time, and first-pass rate across NPI and Mass Production phases
• Define, develop, and validate comprehensive manufacturing and test requirements for advanced compute and GPU systems
• Lead complex hardware debugging efforts, driving root cause analysis and Failure Analysis and Corrective Actions (FACA)
• Manage the technical transition of products from prototype builds to high-volume manufacturing
• Travel internationally to supplier sites (up to 25%) to manage hardware validation and foster technical partnerships
• Partner with cross-functional teams to drive power optimizations and performance tuning during manufacturing validation

Requirements

• 12+ years of experience in manufacturing engineering or a related field
• Proven experience leading complex hardware products from NPI through to high-volume Mass Production (MP) launch
• Working knowledge of hardware architecture with hands-on experience in testing and validation of compute and GPU systems
• Background in process development, bring-up, and qualification (Final Assembly, Test, and Packout)
• Experience partnering with stakeholder teams to drive alignment on technical decisions

Preferred Qualifications

• Experience managing relationships with international contract manufacturers
• Advanced degree in Electrical, Mechanical, or Manufacturing Engineering
• Background in reliability engineering methodologies, including accelerated life testing and failure mode analysis
• Experience with quality management systems such as ISO 9001
• Experience with test automation frameworks and manufacturing execution systems (MES)
• Experience with GPU architectures, high-performance computing, or AI/ML infrastructure hardware

About the Company

Meta builds technologies that help people connect, find communities, and grow businesses. As we move beyond 2D screens toward immersive experiences like augmented and virtual reality, our Manufacturing Quality Engineering team is building the infrastructure that powers AI at global scale.