{"id":3305994,"url":"https://alion.io/job/meta-failure-analysis-engineer","title":"Failure Analysis Engineer","company":{"id":20,"name":"Meta","domain":"meta.com","url":"https://alion.io/company/meta","size_band":"5000+","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Career sitemap","truth_index":{"grade":"B","score":77,"open_postings":241,"ghost_share":0,"stale_share":0.934,"repost_share":0,"time_to_fill_p50_days":37,"computed_at":"2026-10-31T05:58:55Z"}},"role":"Industrial Engineering","role_family":"Industrial Engineering","seniority":"senior","employment_type":"full_time","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Fremont, United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":162000,"max_usd":306000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":6333},"experience_years_min":6,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Physical AI","optional":false}],"status":"live","first_seen_at":"2026-10-26T22:17:34Z","employer_posted_date":"2026-10-26","last_verified_at":"2026-11-01T01:17:42Z","board_verified":true,"closed_at":null,"days_open":5,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":5},"description":"Be part of a centralized Product Integrity Team. This is an opportunity to influence the future of Meta’s infrastructure as we build FA framework from the ground up that is needed to scale our current services and support long term goal of meeting Artificial General Intelligence (AGI).Candidate gets to work on state of the projects including custom ASICs, physical AI and strengthen failure analysis relationships with worldwide supply and manufacturing base. Candidate will be applying knowledge of system hardware, electrical, and materials analysis to perform failure analysis across different issues and provide end-to-end analysis to arrive at corrective actions.\nResponsibilities\nResponsible for all aspects of identifying and characterizing failures on Data Center HW that leads to successful identification of root cause of the failure Work with cross functional teams from all disciplines to determine and/or discuss root cause Utilize FA equipment such as Optical/Digital Microscopes, Oscilloscopes, X-ray, and SEM to successfully complete FA projects Work closely with HW Reliability to root-cause reliability failures Recreate and identify failures observed in engineering, production, and field as needed for efficient fault isolation Debugging thermal related PCB and electrical module failures Develop corrective actions for various failures observed based on Physics of Failure methodology and validate the same Taking additional steps to ensure prevention of similar issues from repeating on new NPI programs Work cross-functionally across hardware teams to advance and land new technologies in the data centers Quantify FA in terms of improvements in yield, reliability, serviceability, manufacturability, testability, capacity, and cost when needed Validate and verify supplier and vendor FA SOP creation for vendors and suppliers to repeat similar FA analysis if and when needed Lab organization and detailed documentation leading to effective FA reports\nQualifications\nBachelors in Electrical or Mechanical engineering or Materials Science with 6+ years of failure analysis experience Hands-on experience with SEM, p-FIB, mechanical polishing, dicing, EDS, mechanical probing, EBIC/EBAC, OBIRCH, LADA, TIVA, etc Systematic FA approach application and experience to methodically break down a system or process into subparts to isolate failures and troubleshoot to a component level Experience with the use of eFA equipment including Oscilloscopes, spectrum analyzers, frequency generators, source meters, and multimeters Fault localization skills for custom Si/ASICs Masters or PhD in Electrical Engineering or Materials Science with direct Data Center HW FA experience Experience analyzing datacenter failures (rack level hardware and/or datacenter infrastructure hardware) Fault localization skills for PCIE gen 5/6 and DDR gen 5/6 Demonstrated ability to integrate AI tools to optimize/redesign workflows and drive measurable impact (e.g., efficiency gains, quality improvements)","description_format":"text","description_chars":3004,"description_truncated":false,"requirements":{"experience_years_min":6,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":{"level":"bachelor","optional":false},"security_clearance":false,"languages":[]},"benefits":[],"hiring_locations":[],"hiring_excludes":[],"relocation_offered":false,"industries":["Advertising","Virtual & Augmented Reality","Digital 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