Full Description

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Our vision is to transform how the world uses information to enrich life for all .

Micron Technology is a world leader in innovating memory and storage solutions that accelerate the transformation of information into intelligence, inspiring the world to learn, communicate and advance faster than ever.

As a Product Quality Assurance Engineer at Micron Technology, Inc., you will be responsible for driving product quality improvements through electrical failure analysis (EFA), data mining, and new part qualification support. You will collaborate with cross-functional teams including Process Integration, Product Engineering, and Manufacturing to enhance yield, reliability, and manufacturability. This role focuses on improving internal quality metrics such as NCD, Product Grade, PTS, and GSPEC, while also monitoring global dashboards and reliability metrics. You will apply structured problem-solving methodologies and advanced reliability principles to identify and mitigate quality risks, ensuring Micron products exceed customer expectations.

Responsibilities

Drive product quality improvements through EFA, data analysis, and qualification support. Monitor and improve internal quality metrics including NCD, Product Grade, PTS, and GSPEC. Lead root cause analysis using structured problem-solving tools such as 8D and FMEA. Collaborate with engineering and manufacturing teams to implement containment and corrective actions. Analyze multiple data sources to identify reliability issues and provide customer feedback. Ensure data integrity and proactively address potential quality concerns. Link product layout to process marginality and test performance. Apply knowledge of electrical device characteristics and reliability failure models.

Minimum Qualifications

Bachelor's degree in Electrical, Electronics, Materials Science, Micro-Electronics, Physics, or a related field. Must also be willing/able to work weekends or evenings, as needed. Understanding semiconductor/manufacturing environments/process flows and reliability failure models, effective priority-setting, knowledge of semiconductor device physics, CMOS, DRAM/Flash memory electrical operation, and Probe/Test flows, an understanding of reliability failure models, Familiarity with DRAM/Flash memory operation, probe/test flows, and semiconductor process environments. Strong analytical (statistical methods to perform data analysis, knowledge of Failure Modes and Effects Analysis -FMEA, understanding of inline defect detection and failure analysis techniques), problem-solving (understanding of problem-solving methodologies such as 8D, Kepner-Tregoe or Six Sigma)