System Failure Analysis Engineer

**Summary:** Meta is seeking a System Failure Analysis Engineer to join our Hardware Quality and Reliability Engineering team, focusing on Early Field Failure Analysis (EFFA) and Ongoing Field Failure Analysis (OFFA) for consumer hardware products including virtual reality headsets, augmented reality glasses, and wearable devices. In this role, you will investigate hardware failures from field returns and customer-reported issues, identify root causes, and drive corrective actions that improve product quality and reliability. You will leverage strong software development skills and AI tool-building capabilities to create automated analysis solutions and intelligent diagnostic systems. You will partner closely with hardware design, manufacturing, field support, and reliability engineering teams to ensure Meta's next-generation devices meet the highest standards of performance and durability. **Required Skills:** System Failure Analysis Engineer Responsibilities: 1. Perform Early Field Failure Analysis (EFFA) and Ongoing Field Failure Analysis (OFFA) on returned or customer-reported hardware units across Meta's consumer device portfolio, including VR headsets, AR glasses, and wearable electronics 2. Build and deploy AI-powered tools and machine learning models to automate failure classification, root cause prediction, and anomaly detection in field failure data 3. Develop software scripts, data pipelines, and analysis tools using Python or similar languages to streamline failure analysis workflows and improve diagnostic efficiency 4. Apply fault isolation techniques such as electrical characterization, boundary scan, and functional diagnostics to identify failure modes at the board, component, and system level 5. Conduct physical failure analysis using tools such as optical microscopy, scanning electron microscopy, cross-sectioning, and X-ray inspection to determine root cause 6. Design and implement automated test and diagnostic systems that leverage AI and machine learning to enhance failure detection and triage capabilities 7. Document failure analysis findings in structured reports, including failure mode classification, root cause determination, and recommended corrective actions 8. Collaborate with hardware design and reliability engineering teams to translate failure analysis findings into design improvements and process changes 9. Track and analyze failure trends using quality data systems and custom-built analytical tools to identify systemic issues and prioritize investigation efforts 10. Communicate failure analysis results and quality insights to engineering leaders and stakeholders across varying levels of technical background **Minimum Qualifications:** Minimum Qualifications: 11. Currently has, or is in the process of obtaining a Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience. Degree must be completed prior to joining Meta 12. 2+ years of experience in hardware failure analysis, hardware quality engineering, or reliability engineering for consumer electronics or similar electromechanical systems 13. 2+ years of hands-on experience with failure analysis techniques including electrical fault isolation, optical and electron microscopy, X-ray inspection, or cross-sectioning 14. 2+ years of experience with programming languages such as Python, C++, or similar for data analysis, automation, or tool development 15. Experience building data analysis pipelines, automation scripts, or diagnostic tools to support engineering workflows 16. Experience interpreting schematic diagrams, PCB layouts, and component datasheets to support system-level fault isolation 17. Experience documenting and communicating technical failure analysis findings to cross-functional engineering teams and stakeholders **Preferred Qualifications:** Preferred Qualifications: 18. Demonstrated ability to integrate AI tools to optimize/redesign workflows and drive measurable impact (e.g., efficiency gains, quality improvements) 19. Experience developing AI or machine learning models for failure prediction, classification, or anomaly detection 20. Experience adhering to and implementing responsible, ethical AI practices (e.g., risk assessment, bias mitigation, quality and accuracy reviews) 21. Familiarity with reliability testing methodologies such as HALT, HASS, or accelerated life testing in the context of consumer hardware qualification 22. Experience with Early Field Failure Analysis (EFFA) or Ongoing Field Failure Analysis (OFFA) programs for consumer electronics 23. Demonstrated ongoing AI skill development (e.g., prompt/context engineering, agent orchestration) and staying current with emerging AI technologies 24. Experience building internal tools, dashboards, or automated systems to improve engineering team productivity 25. Experience with failure analysis of wearable devices, AR/VR hardware, or compact consumer electronics with complex system-on-chip or flexible circuit assemblies 26. Experience using statistical quality tools (e.g., Pareto analysis, Weibull analysis, control charts) to identify and prioritize systemic hardware failure trends **Public Compensation:** $118,000/year to $170,000/year + bonus + equity + benefits **Industry:** Internet **Equal Opportunity:** Meta is proud to be an Equal Employment Opportunity and Affirmative Action employer. We do not discriminate based upon race, religion, color, national origin, sex (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender, gender identity, gender expression, transgender status, sexual stereotypes, age, status as a protected veteran, status as an individual with a disability, or other applicable legally protected characteristics. We also consider qualified applicants with criminal histories, consistent with applicable federal, state and local law. Meta participates in the E-Verify program in certain locations, as required by law. Please note that Meta may leverage artificial intelligence and machine learning technologies in connection with applications for employment. Meta is committed to providing reasonable accommodations for candidates with disabilities in our recruiting process. If you need any assistance or accommodations due to a disability, please let us know at accommodations-ext@meta.com.