System Failure Analysis Engineer
- Pay
- $118,000 – $170,000 per year
- Location
- Sunnyvale, CA · On-site
- Job type
- Full-time
- Level
- Senior
- Experience
- 2+ years
- Education
- Bachelor's degree
- Listed
- 28 days ago
Skills & highlights for this role
- failure analysis
- electrical fault isolation
- X-ray inspection
- Python
Also useful
- HALT
- HASS
- Weibull analysis
- machine learning
About the role
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- System Failure Analysis Engineer
- System Failure Analysis Engineer
- Sunnyvale, CA
- Engineering
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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.
System Failure Analysis Engineer Responsibilities
- 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
- Build and deploy AI-powered tools and machine learning models to automate failure classification, root cause prediction, and anomaly detection in field failure data
- Develop software scripts, data pipelines, and analysis tools using Python or similar languages to streamline failure analysis workflows and improve diagnostic efficiency
- Apply fault isolation techniques such as electrical characterization, boundary scan, and functional diagnostics to identify failure modes at the board, component, and system level
- Conduct physical failure analysis using tools such as optical microscopy, scanning electron microscopy, cross-sectioning, and X-ray inspection to determine root cause
- Design and implement automated test and diagnostic systems that leverage AI and machine learning to enhance failure detection and triage capabilities
- Document failure analysis findings in structured reports, including failure mode classification, root cause determination, and recommended corrective actions
- Collaborate with hardware design and reliability engineering teams to translate failure analysis findings into design improvements and process changes
- Track and analyze failure trends using quality data systems and custom-built analytical tools to identify systemic issues and prioritize investigation efforts
- Communicate failure analysis results and quality insights to engineering leaders and stakeholders across varying levels of technical background
Minimum Qualifications
- 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
- 2+ years of experience in hardware failure analysis, hardware quality engineering, or reliability engineering for consumer electronics or similar electromechanical systems
- 2+ years of hands-on experience with failure analysis techniques including electrical fault isolation, optical and electron microscopy, X-ray inspection, or cross-sectioning
- 2+ years of experience with programming languages such as Python, C++, or similar for data analysis, automation, or tool development
- Experience building data analysis pipelines, automation scripts, or diagnostic tools to support engineering workflows
- Experience interpreting schematic diagrams, PCB layouts, and component datasheets to support system-level fault isolation
- Experience documenting and communicating technical failure analysis findings to cross-functional engineering teams and stakeholders
Preferred Qualifications
- Demonstrated ability to integrate AI tools to optimize/redesign workflows and drive measurable impact (e.g., efficiency gains, quality improvements)
- Experience developing AI or machine learning models for failure prediction, classification, or anomaly detection
- Experience adhering to and implementing responsible, ethical AI practices (e.g., risk assessment, bias mitigation, quality and accuracy reviews)
- Familiarity with reliability testing methodologies such as HALT, HASS, or accelerated life testing in the context of consumer hardware qualification
- Experience with Early Field Failure Analysis (EFFA) or Ongoing Field Failure Analysis (OFFA) programs for consumer electronics
- Demonstrated ongoing AI skill development (e.g., prompt/context engineering, agent orchestration) and staying current with emerging AI technologies
- Experience building internal tools, dashboards, or automated systems to improve engineering team productivity
- Experience with failure analysis of wearable devices, AR/VR hardware, or compact consumer electronics with complex system-on-chip or flexible circuit assemblies
- Experience using statistical quality tools (e.g., Pareto analysis, Weibull analysis, control charts) to identify and prioritize systemic hardware failure trends
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Meta builds technologies that help people connect, find communities, and grow businesses. When Facebook launched in 2004, it changed the way people connect. Apps like Messenger, Instagram and WhatsApp further empowered billions around the world. Now, Meta is moving beyond 2D screens toward immersive experiences like augmented and virtual reality to help build the next evolution in social technology.
People who choose to build their careers by building with us at Meta help shape a future that will take us beyond what digital connection makes possible today—beyond the constraints of screens, the limits of distance, and even the rules of physics.
For those who live in or expect to work from California if hired for this position, please click here for additional information.
United States of America: $118,000/year to $170,000/year + bonus + equity + benefits
Individual compensation is determined by skills, qualifications, experience, and location. Compensation details listed in this posting reflect the base hourly rate, monthly rate, or annual salary only, and do not include bonus, equity or sales incentives, if applicable. In addition to base compensation, Meta offers benefits. Learn more about benefits at Meta.
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From Meta's careers page, first listed on Rolev.ai on October 12, 2026. Rolev.ai is not the employer.
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Common questions
What is the salary for the System Failure Analysis Engineer role at Meta?
The System Failure Analysis Engineer posting at Meta states compensation of $118,000 – $170,000 per year. It is listed as a full-time position. Final pay may depend on location, experience, and interview evaluation on Meta's official career site.
Where is the System Failure Analysis Engineer job at Meta located?
This System Failure Analysis Engineer position at Meta is located in Sunnyvale, CA (On-site). Always check Meta's application page for specific state eligibility or relocation policies.
What qualifications are required for System Failure Analysis Engineer at Meta?
For the System Failure Analysis Engineer role, Meta highlights 2+ years of relevant experience; a bachelor's degree; experience with failure analysis, electrical fault isolation, X-ray inspection, Python. Rolev.ai can score your existing resume against these requirements and show any skill gaps before you apply.
How do I apply for the System Failure Analysis Engineer position at Meta?
This listing links directly to Meta's application page. You can apply directly on Meta's site, or use Rolev.ai to check your resume fit, generate a zero-hallucination tailored resume and cover letter for this posting, and autofill the application form in 1 click with the Rolev.ai Chrome extension. You always review the form and press Submit yourself.