AI-Driven NAND Probe & Yield Engineering Intern

Micron Technology, Inc; Singapore; On-site; SGD 17,000 - 23,000; Full time

Job summary

Micron Technology, Inc. invites a NAND Product Engineering Intern to join the AI-enabled wafer probe test optimization and yield analytics project in Singapore.

You will study wafer probe test strategies, analyze yield data, and apply AI-driven methods to improve test efficiency and data quality. Gain exposure to NAND technologies, wafer-level testing, and cross-functional collaboration with Design, Process, and Manufacturing teams.

Qualifications

• Strong analytical, problem-solving, and technical communication skills.
• Familiarity with Python, SQL, MATLAB, or equivalent programming and data analysis tools.
• Familiarity with statistical analysis, data visualization, machine learning, or AI-enabled workflows.
• Willingness to learn and apply Generative AI for data exploration and automation.

Responsibilities

• Study wafer probe test flows, screening methodologies, and product performance indicators.
• Analyze probe, wafer-level, and device-level datasets to identify yield trends, anomalies, and failure signatures.
• Develop an AI-enabled analytical or automation solution for yield analysis, anomaly detection, data visualization, or workflow improvement.
• Deliverables include a documented analysis, data visualizations, and an AI-enabled prototype or methodology.
• Participate in technical reviews involving test structures and observability features, trims, and yield optimization opportunities.

Skills

Analytical thinking

Problem-solving

Technical communication

Python

SQL

MATLAB

Statistics

Machine learning

Generative AI

Education

Bachelor’s / Master’s / PhD in Electrical Engineering or related

Semiconductor physics

Tools

Python

SQL

MATLAB

Job description

Micron Technology, Inc. invites a NAND Product Engineering Intern to join the AI-enabled wafer probe test optimization and yield analytics project in Singapore.

You will study wafer probe test strategies, analyze yield data, and apply AI-driven methods to improve test efficiency and data quality. Gain exposure to NAND technologies, wafer-level testing, and cross-functional collaboration with Design, Process, and Manufacturing teams.