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Product Quality Assurance & Quality Engineering (PQA / PQE)

Micron Technology

Taichung MTB, TaiwanFull TimeMidH-1B sponsor company
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Location
Taichung MTB, Taiwan
Employment
Full Time
Work model
On-Site
Level
Mid
H-1B history
69 approvals (FY2023)
Posted

Skills

GenAIMachine LearningPower BIPythonSQL

About this role

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 & Quality Engineering (PQA / PQE) in MTB, you will be responsible for driving product and in-line process quality for Back End manufacturing. This role focuses on establishing effective quality processes and data-driven methodologies to identify, analyze, and mitigate quality risks across assembly, test, and probe operations. You will work closely with Manufacturing, Assembly/Test Engineering, Product Engineering, and Global Quality teams to improve outgoing product quality, manage deviations, support qualification activities, and ensure robust correlation between in-line inspection, probe results, and customer quality requirements, enabling Micron to deliver best-in-class product quality. Additionally, this role will leverage AI, advanced analytics, and digital technologies to transform quality management from reactive issue resolution to predictive and preventive quality intelligence. The role will drive systemic root cause learning, quality knowledge management, and lesson-learned fan-out across both High Volume Manufacturing (HVM) and New Product Introduction (NPI) programs, enabling quality-by-design practices throughout the product lifecycle.   Responsibilities and Tasks Drive product and process quality improvement through structured problem solving, data analysis, and continuous improvement initiatives. Leverage AI, advanced analytics, and quality intelligence systems to identify systemic failure modes, accelerate root cause learning, automate lesson-learned fan-out, and drive preventive actions across HVM and NPI products. Transform deviations, MRB learnings, and 8D findings into scalable risk prevention mechanisms, enterprise-wide quality knowledge, and quality-by-design improvements. Collaborate with Manufacturing, Assembly/Test Engineering, Product Engineering, Global Quality, and Central teams to resolve quality issues and drive site-level quality improvements. Develop, manage, and communicate quality metrics, dashboards, and analytical insights to monitor performance, identify trends, and support data-driven decision making. Lead quality risk assessments, root cause investigations, and implementation of effective corrective and preventive actions (CAPA). Manage quality-deviated products and lead MRB activities to ensure appropriate disposition of non-conforming products and prevent unintended use or shipment. Implement and promote effective 8D methodologies, structured problem-solving practices, and quality management processes to ensure timely issue resolution and recurrence prevention. Utilize data mining, statistical analysis, workflow automation, and AI-assisted engineering tools to improve quality effectiveness, operational efficiency, and engineering productivity. Support product and process qualification activities, customer audits, and cross-functional stakeholder engagement to ensure alignment with quality objectives and customer requirements.

Education

Master's degree or equivalent experience in Mechanical, Electrical/Electronics, Materials, Physics, Chemistry, or related fields.

Experience

Preferred experience in the semiconductor industry or related areas including product quality, process engineering, manufacturing, research, or development. Preferred proficiency in English and Mandarin, both written and verbal. Experience with data analytics and visualization tools such as JMP, Power BI, SQL, Python, or equivalent platforms. Familiarity with AI-assisted engineering tools, workflow automation, machine learning, Generative AI, or digital manufacturing solutions is preferred. Experience utilizing AI-based tools for technical reporting, knowledge management, root

Listing verified . Applications go through the company's official careers site.

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