RDA Quality Engineer: Defect & Metrology Lead

Micron Technology, Inc; Boise (ID); On-site; USD 90,000 - 120,000; Full time

Benefits offered by this job

Medical/dental/vision plans

Paid time off

Paid holidays

Relocation TBD

Job summary

Micron Technology, Inc. is seeking an ID1 RDA Quality Engineer to develop quality systems for defect detection and metrology across our global manufacturing network. You will monitor quality metrics, lead corrective actions, and collaborate with sites, process, yield, and data science teams.

The role focuses on applying SPC, FMEA, and AI-enabled analytics to improve process monitoring, fault detection, and product yield. A Bachelor's in a technical field is required.

Qualifications

• Bachelor's degree in a technical field is required.
• Experience analyzing manufacturing, process, quality, or engineering data to identify trends.
• Understanding of SPC, root cause analysis, and quality management principles.
• Strong written and verbal communication with cross-functional teams.

Responsibilities

• Develop, implement, and maintain quality control systems and BKMs for RDA/Metrology.
• Monitor quality performance metrics and SPC compliance; drive corrective actions.
• Lead or support excursion mitigation, FMEA, sampling strategy, and audits.
• Collaborate with global teams to align quality methods and transfer technology to HVM.
• Use AI-enabled tools and data analytics to improve monitoring and decision making.

Skills

Data analysis

Statistical methods (SPC)

Root cause analysis

Technical communication

AI-enabled tools familiarity

Education

Bachelor's degree in Engineering/Materials Science/Physics/Chemistry/Data Science

Master's degree in Engineering/Materials Science/Data Science

Tools

AI analytics tools

Job description

Micron Technology, Inc. is seeking an ID1 RDA Quality Engineer to develop quality systems for defect detection and metrology across our global manufacturing network. You will monitor quality metrics, lead corrective actions, and collaborate with sites, process, yield, and data science teams.

The role focuses on applying SPC, FMEA, and AI-enabled analytics to improve process monitoring, fault detection, and product yield. A Bachelor's in a technical field is required.