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The ideal candidate will have a good understanding of AI (Artificial Intelligence) /Data Center products, excellent analytical skills with a strong structured problem-solving background and proven experience in failure root cause resolution. Your hands-on failure analytical skills and strong quality mindset are essential as you will be working to drive GPU Data Center products quality improvement initiatives and programs.
Detailed failure analysis, identifying root-cause of customer reported issues – Perform PCB-level analysis to isolate faults for physical FA on NVIDIA Data Center Compute Modules.
Define appropriate characterization techniques to root cause complex problems
Continuously develop sophisticated analysis tools and methodology to screen identified failure modes and expand FAcapacity.
Apply knowledge of system design, electrical engineering and PCBA manufacturing to propose containment and corrective action fordesign/production/supplier.
Assist in generating 8D failure analysis reports and verify/characterize corrective actions’ effectiveness.
Quality representative to internal teams, supporting activities for customer quality and internal quality requirements.
Master’s degree or above in Electronic Engineering or related fields or equivalent experience.
8+ years of Hands-on experience in PCB level hardware verification/debug and signal integrity measurement
Knowledge on AI/Data Center products design verification and validation, production testing, and statistical analysis
Proficiency in Linux system and Linux Shell Scripts. Experience with scripting languages such as Python is a plus.
Familiarity with data center deployment and bus standards/protocols like PCIe, IPMI, Redfish is a plus.
Exceptional problem solving and Failure Analysis, strong attention to detail and analytical thinking.
Good communication and documentation skills in English
You will also be eligible for equity and .
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