Intern - Data-Driven Photo-Process Engineer

Micron Technology; Singapore; On-site; SGD 20,000 - 27,000; Full time

Job summary

Micron Technology, Inc. in Singapore is seeking a university intern for a five-month, full-time internship in Fab10 High-Volume Manufacturing Photo Process and Equipment Engineering.

You will work on automating Non-Zero-Offset analysis using Python, statistics, and machine learning to improve workflow efficiency. You will study end-to-end workflow, analyze historical data, develop a Python-based framework, and prototype an automated dashboard to support engineering decisions.

Qualifications

• Proficiency in Python for data preparation, analysis, modeling, and visualization.
• Basic knowledge of statistics, machine learning, or applied data analytics.
• Strong analytical thinking, structured problem-solving, and ability to work with large datasets.
• Effective technical communication skills and familiarity with approved AI tools or AI-Enabled analytical workflows.

Responsibilities

• Study the high-volume manufacturing photo-process flow and Non-Zero-Offset control methodology with relevant engineering subject matter experts.
• Prepare and analyze historical Non-Zero-Offset, inline, recipe, and metrology datasets using Python-based data pipelines.
• Develop and evaluate statistical or machine-learning approaches for identifying Non-Zero-Offset patterns, trigger conditions, and potential risk indicators.
• Design and prototype an automated logic flow, visualization, or dashboard that improves Non-Zero-Offset review and engineering decision-making.

Skills

Python

Statistics

ML basics

Data analysis

Education

Related engineering or data science degree

Tools

Pandas

NumPy

Jupyter

Job description

Micron Technology, Inc. in Singapore is seeking a university intern for a five-month, full-time internship in Fab10 High-Volume Manufacturing Photo Process and Equipment Engineering.

You will work on automating Non-Zero-Offset analysis using Python, statistics, and machine learning to improve workflow efficiency. You will study end-to-end workflow, analyze historical data, develop a Python-based framework, and prototype an automated dashboard to support engineering decisions.