Intern - F10 PHOTO PEE

1100 Micron SemiAsiaOP Pte Ltd; Singapore; On-site; SGD 20,000 - 27,000; Full time

Job summary

Micron Technology, Inc. in Singapore invites applications for an AI-Enabled Quality Drift Detection and Engineering Workflow Automation internship within the Photolithography Process and Equipment Engineering team.

You will work on advanced data analytics and ML to improve quality metrics and drift detection. As a full-time internship lasting five months from January to May 2027, high-performing students may be considered for future opportunities.

Qualifications

• Pursuing a degree in engineering, statistics, mathematics, computer science, data science, or related field.
• Strong analytical thinking and problem-solving skills.
• Experience with data analytics or ML concepts is a plus.

Responsibilities

• Develop analytical models to monitor quality metrics and detect drift.
• Apply ML and multivariable analysis to large-scale datasets.
• Create automated workflows and visualizations to communicate results.
• Document methods, results, and recommendations in final report.

Skills

Strong analytical thinking

Data analytics

Statistics

Programming in R or Python

ML/AI familiarity

Data visualization

Education

Degree in Engineering, Statistics, Mathematics, Computer Science, Data Science

Tools

R

Python

Job description

Our vision is to transform how the world uses information to enrich life for all. Join an inclusive team passionate about one thing: using their 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. We do it all while committing to integrity, sustainability, and giving back to our communities. Because doing so can fuel the very innovation we are pursuing.

Location

Micron Singapore, Fab 10 (1 North Coast Drive, Singapore 757432)

Department

Photolithography Process and Equipment Engineering

Project Title

AI-Enabled Quality Drift Detection and Engineering Workflow Automation

Project Description

Advanced data analytics and machine learning are increasingly used in semiconductor manufacturing to improve efficiency, process control, and quality performance. This internship project focuses on applying data analytics and machine learning techniques to large-scale quality datasets for faster detection of quality-metrics drift. The intern will contribute to an end-to-end solution covering data querying, preprocessing, analytics, modelling, and results visualization.

Objective of the Project

• Develop analytical models for monitoring key quality metrics and detecting potential drift.
• Apply machine learning and multivariable analysis to large-scale test and measurement data.
• Create automated workflows that improve engineering productivity and analytical efficiency.
• Develop visualizations that communicate model results and quality trends effectively.

Opportunities for Full Time Employment

High-performing interns who demonstrate strong technical capability, learning agility, and successful project outcomes may be considered for future internship or full-time employment opportunities, subject to business needs and hiring requirements.

Project Scope

• Explore machine learning techniques for feature selection, modelling, and simulation.
• Analyze large-scale quality, test, and measurement datasets.
• Perform multivariable optimization and curve turning-point detection.
• Develop AI-Enabled workflows and visualization tools that improve engineering productivity.

Learning Opportunities

• Gain hands-on experience with semiconductor manufacturing data analytics.
• Learn industrial applications of machine learning, predictive modelling, simulation, and optimization.
• Develop practical skills in data querying, preprocessing, analytics, and visualization.
• Collaborate with cross-functional engineering teams and subject-matter experts.
• Explore Artificial Intelligence and workflow-automation applications within Process and Equipment Engineering.

Deliverables

• Analytical models for monitoring selected quality metrics.
• An early quality-drift detection methodology and visualization solution.
• An automated workflow addressing a selected engineering-productivity opportunity.
• Final project documentation and presentation summarizing the methods, results, limitations, and recommendations.

Impact of the Project

• Improve visibility into quality-metrics performance and potential process drift.
• Enable earlier identification of abnormal quality trends.
• Enhance product and process control through data-driven insights.
• Improve engineering productivity through AI-Enabled workflow automation.

Skillsets Required

• Strong analytical thinking and general problem-solving skills.
• Background in data analytics, statistics, or large dataset interpretation.
• Programming experience in R, Python, or a similar language.
• Familiarity with machine learning, data visualization, or optimization concepts.
• Familiarity with Artificial Intelligence tools, AI Assistants, or AI-Enabled workflows is advantageous.

Course of Interest

The ideal candidate should be pursuing a Degree in Engineering, Statistics, Mathematics, Computer Science, Data Science, or another data analytics-related discipline.

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.

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. To learn more, please visit micron.com/careers

All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, veteran or disability status.

To request assistance with the application process and/or for reasonable accommodations, please contact [e-mail]

Micron Prohibits the use of child labor and complies with all applicable laws, rules, regulations, and other international and industry labor standards.

Micron does not charge candidates any recruitment fees or unlawfully collect any other payment from candidates as consideration for their employment with Micron.