Intern- Manufacturing Test Engineer

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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 990 Bendemeer Road, Singapore 339942 (MSB)

Department Manufacturing Test, MSB

Project Title Faster Manufacturing Metrics Analysis and Drift Detection Using Advanced Data Analytics and Machine Learning

Project Description Data analytics and machine learning are used in manufacturing operations to improve efficiency and provide greater visibility into production-line health. Large volumes of data are generated from electrical tests, physical tests, and manufacturing measurements, creating opportunities for faster analysis and earlier detection of abnormal performance. This internship project focuses on developing an end-to-end analytical solution covering data querying, preprocessing, feature engineering, modelling, and results visualization. The intern will apply advanced analytics and machine learning techniques to manufacturing data to improve metrics analysis and identify potential performance drift. Through this project, the intern will gain exposure to industrial data analytics, predictive modelling, simulation, optimization, and visualization techniques used in semiconductor manufacturing.

Objective of the Project

• Develop an end-to-end analytics solution for faster manufacturing metrics analysis.

• Apply machine learning to identify important features, model manufacturing performance, and detect potential drift.

• Explore correlations across test, measurement, inline, and probe datasets.

• Evaluate AI-Enabled methods that improve data analysis, visualization, and engineering decision-making.

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

• Apply data analytics, machine learning, and Artificial Intelligence techniques for feature selection, modelling, and simulation.

• Analyze correlations across electrical test, physical measurement, inline, and probe data.

• Explore multivariable optimization methods to identify key drivers of manufacturing performance.

• Develop visualizations or dashboards to communicate analytical findings and model results.

Learning Opportunities

• Gain hands-on experience with large-scale semiconductor manufacturing datasets.

• Learn industrial applications of machine learning, predictive modelling, simulation, and optimization.

• Develop practical skills in data querying, preprocessing, feature engineering, model evaluation, and visualization.

• Collaborate with engineering teams and subject-matter experts to understand manufacturing challenges and translate data into actionable insights.

• Explore the use of AI-Enabled tools and AI Assistants to improve analytical productivity and technical reporting.

Deliverables

• Predictive models for manufacturing metrics analysis and monitoring.

• Early drift-detection methodology with appropriate model evaluation.

• End-to-end analytical workflow covering data extraction, preprocessing, modelling, and visualization.

• Final project documentation and presentation summarizing findings, limitations, and recommendations.

Impact of the Project

• Enable faster analysis of manufacturing metrics and production-line health.

• Improve the early identification of performance drift and abnormal trends.

• Enhance data-driven decision-making within Manufacturing Test operations.

Skillsets Required

• Strong analytical thinking and general problem-solving skills.

• Experience with data analytics and programming languages such as Python or R.

• Familiarity with machine learning, statistical analysis, modelling, and data visualization.

• Proficiency in Artificial Intelligence or familiarity with AI-Enabled applications and workflows is advantageous.

Course of Interest The ideal candidate should be pursuing a Degree in Engineering, Data Analytics, Statistics, Mathematics, Computer Science, or a related field.

Duration of Period The ideal candidate should be able to commit to a full time internship period of at least 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 hrsupport_sg@micron.com

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.

AI alert: Candidates are encouraged to use AI tools to enhance their resume and/or application materials. However, all information provided must be accurate and reflect the candidate's true skills and experiences. Misuse of AI to fabricate or misrepresent qualifications will result in immediate disqualification.

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