RDA Process Engineer: AI-Driven Defect & Yield

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

Job summary

Micron Technology is seeking a RealTime Defect Analysis (RDA) HVM Process Engineer to tackle defect-related challenges on high-volume semiconductor lines. You will work with defect inspection systems, analytics, and cross-functional teams to reduce defects, improve yield, and enable data-driven manufacturing decisions.

The role emphasizes collaboration with Process Integration, Process Development, Yield Enhancement, and Data Science teams, using AI-enabled tools and statistical methods to

Qualifications

• Bachelor's degree in a STEM field and foundational data analytics aptitude.
• Ability to analyze complex process and defect data to identify root causes.
• Experience or interest in semiconductor manufacturing environments.

Responsibilities

• Review inspection data and metrics to identify defect trends and yield-impacting issues.
• Investigate excursions and support root-cause analysis and corrective actions.
• Monitor process health indicators and maintain stability across HVM lines.
• Apply AI-enabled tools and automation to improve problem solving and efficiency.
• Collaborate with Process Integration, Yield, and Data Science teams across sites.
• Develop methods and visualizations to enhance process visibility and decision making.
• Support technology transfer and continuous improvement initiatives.

Skills

Analytical skills

Team collaboration

Communication

Willingness to learn

Data analysis

Education

Bachelor's degree in Electrical Engineering, Chemical Engineering, Materials Science and Engineering, Mechanical Engineering, Physics, Computer Engineering, Data Science, or related STEM

Tools

Python

SQL

JMP

Power BI

MATLAB

R

Job description

Micron Technology is seeking a RealTime Defect Analysis (RDA) HVM Process Engineer to tackle defect-related challenges on high-volume semiconductor lines. You will work with defect inspection systems, analytics, and cross-functional teams to reduce defects, improve yield, and enable data-driven manufacturing decisions.

The role emphasizes collaboration with Process Integration, Process Development, Yield Enhancement, and Data Science teams, using AI-enabled tools and statistical methods to