Intern - RDA (Real-Time Defect Analysis)

Internship: AI-Enabled Defect Analytics and Yield Investigation

Location: F10N

Department: Real-Time Defect Analysis

Join an inclusive team passionate about using expertise in the relentless pursuit of innovation for customers and partners. The solutions we build help make everything from virtual reality experiences to breakthroughs in neural networks possible, while committing to integrity, sustainability, and giving back to our communities.

Project Description

The intern will undertake an engineering project focused on defect analysis and semiconductor yield improvement. Under engineer guidance, the intern will analyze defect and yield data, investigate selected excursions, and develop analytics or AI-enabled solutions that improve analysis efficiency and accelerate root-cause identification.

Objective of the Project

• Identify defect and yield trends using manufacturing data.
• Apply statistical analysis to a selected yield investigation.
• Develop an analytics, automation, or Artificial Intelligence solution.
• Generate data-driven findings and improvement recommendations.

Project Scope

• Analyze defect, yield, and excursion data to identify trends and correlations.
• Investigate selected wafer, lot, tool, and process-related yield issues.
• Develop dashboards, scripts, or AI-enabled workflows for defect analysis.
• Collaborate with engineering teams to collect and validate relevant data.
• Document methodologies and communicate project findings.

Learning Opportunities

• Gain exposure to semiconductor defect analysis and yield engineering.
• Learn statistical analysis, data visualization, and root-cause investigation methods.
• Develop experience working with manufacturing and engineering datasets.
• Explore Generative AI, an AI Assistant, or Agentic AI for analysis and workflow automation.

Deliverables

• A completed defect or yield investigation with findings and recommendations.
• An analytics dashboard, automation tool, or AI-enabled solution.
• Technical documentation describing the methodology and results.
• An impact assessment covering productivity, cycle time, analysis efficiency, or investigation quality.

Impact of the Project

• Improve visibility of defect and yield patterns.
• Accelerate selected root-cause investigations.
• Reduce repetitive analytical effort through automation.
• Strengthen data-driven decision-making within Real-Time Defect Analysis.

Skillsets Required

• Strong analytical and problem-solving skills.
• Basic knowledge of statistics, data analysis, or semiconductor manufacturing.
• Familiarity with Python, Structured Query Language (SQL), data visualization, or equivalent tools.
• Interest in Generative AI, Agentic AI, or AI-enabled engineering workflows.
• Clear communication and collaboration skills.

Course of Interest

The ideal candidate should be pursuing a degree in Electrical Engineering, Electronics Engineering, Materials Engineering, Data Science, Computer Engineering, or a related technical field.

Duration of Period

The ideal candidate should be able to commit to a full-time internship period of 5 months from Jan to May 2027.

Opportunities for Full Time Employment

Interns may be considered for future internship or full-time employment opportunities based on business needs, role availability, academic completion, and demonstrated capabilities.

About Micron Technology, Inc.

We are an industry leader in innovative memory and storage solutions transforming how the world uses information to enrich life for all. With a relentless focus on our customers, technology leadership, and manufacturing and operational excellence, Micron delivers a rich portfolio of high-performance DRAM, NAND, and NOR memory and storage products through our Micron® and Crucial® brands. Every day, the innovations that our people create fuel the data economy, enabling advances in artificial intelligence and 5G applications that unleash opportunities—from the data center to the intelligent edge and across the client and mobile user experience.