Key skills
AssemblyAIMLProject Management
About this role
Meta's Manufacturing Quality Engineering team is building the infrastructure that powers AI at a global scale. As a Product Quality Engineer on the Hardware Engineering team, you will play a critical role in bringing next-generation AI/ML hardware from concept to mass production directly enabling the compute capacity that drives Meta's products.
This role sits at the intersection of engineering innovation and operations, where you will execute on the manufacturing readiness plan for advanced compute and GPU platforms, partner with design engineers and global manufacturing partners, and help ensure Meta's hardware fleet meets the highest standards of quality and reliability at hyperscale volumes.
Responsibilities
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
* Develop, validate, and implement manufacturing and test requirements for advanced compute and GPU systems from NPI through to mass production (MP)
* Evaluate and enhance test coverage, methodologies, and infrastructure to improve hardware reliability and performance at scale against defined targets
* 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
* Travel internationally to supplier sites (up to 25%) to manage hardware validation, ensure compliance with test requirements, and maintain technical partnerships
* Partner with cross-functional engineering teams on power optimizations and performance tuning for compute and GPU systems during manufacturing validation
* Support the technical transition of products from prototype builds to high-volume manufacturing, contributing to technical discussions to resolve open design and test issues
Qualifications
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)
This role sits at the intersection of engineering innovation and operations, where you will execute on the manufacturing readiness plan for advanced compute and GPU platforms, partner with design engineers and global manufacturing partners, and help ensure Meta's hardware fleet meets the highest standards of quality and reliability at hyperscale volumes.
Responsibilities
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
* Develop, validate, and implement manufacturing and test requirements for advanced compute and GPU systems from NPI through to mass production (MP)
* Evaluate and enhance test coverage, methodologies, and infrastructure to improve hardware reliability and performance at scale against defined targets
* 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
* Travel internationally to supplier sites (up to 25%) to manage hardware validation, ensure compliance with test requirements, and maintain technical partnerships
* Partner with cross-functional engineering teams on power optimizations and performance tuning for compute and GPU systems during manufacturing validation
* Support the technical transition of products from prototype builds to high-volume manufacturing, contributing to technical discussions to resolve open design and test issues
Qualifications
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)