NAND AI Engineer Intern: Yield & Automation

Micron Technology, Inc; Singapore; On-site; SGD 17,000 - 28,000; Full time

Job summary

Micron Technology, Inc. is offering a full-time internship in Singapore within Product Engineering. The project focuses on applying Machine Learning and Agentic AI to semiconductor yield analysis, test optimization, data processing, and workflow automation.

Mentors will guide you through model development, data preparation, and engineering automation across probe, wafer, and manufacturing data. The role includes hands-on experience with structured data analytics, feature engineering, model

Qualifications

• Pursuing a Bachelor's or Master's degree in Computer Science, Electrical Engineering, Electronics Engineering, Computer Engineering, Data Science, Data Analytics, AI, or related field.
• Basic Python programming with Pandas, NumPy, or Scikit-learn.
• Interest in AI agents, Large Language Models, workflow automation, or AI-enabled engineering solutions.
• Strong analytical thinking, problem-solving, curiosity, and willingness to learn.
• Clear written and verbal communication skills, with the ability to collaborate in a cross-functional engineering environment.

Responsibilities

• Develop ML models for yield, reliability, test-time, or cycle-time improvements.
• Design Agentic AI prototypes for engineering use cases like report generation and anomaly detection.
• Prepare, clean, transform, and integrate engineering data for ML workflows.
• Explore integration with engineering platforms and enterprise tools (Jira, Confluence, SharePoint).
• Document project approach, evaluations, limitations, and next steps.

Skills

Python basics

ML concepts

Pandas/NumPy/Scikit-learn

Cross-functional teamwork

Clear communication

Education

Bachelor's or Master's in Computer Science / Electrical Engineering

Tools

TensorFlow or PyTorch

LangChain

Microsoft Copilot Studio

Jira

Confluence

SharePoint

Job description

Micron Technology, Inc. is offering a full-time internship in Singapore within Product Engineering. The project focuses on applying Machine Learning and Agentic AI to semiconductor yield analysis, test optimization, data processing, and workflow automation.

Mentors will guide you through model development, data preparation, and engineering automation across probe, wafer, and manufacturing data. The role includes hands-on experience with structured data analytics, feature engineering, model