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Location

Singapore, F10A

Department

Heterogeneous Integration Group (HIG) – High Bandwidth Memory (HBM) Product Engineering

Project Title

Advanced Manufacturing Analytics for Early Deviation Detection

Project Description

This internship project provides an opportunity to develop advanced analytics solutions that improve visibility into manufacturing performance and process health for High Bandwidth Memory (HBM) products. The intern will work with large-scale engineering datasets to uncover patterns, identify emerging process deviations, and generate actionable insights that enhance product quality, reliability, and manufacturing outcomes.

The project combines data analytics, statistical modeling, machine learning, and AI-Enabled methodologies to detect abnormal trends at an earlier stage of the manufacturing lifecycle. Through this experience, the intern will gain exposure to semiconductor product engineering while applying modern data science and Agentic AI techniques to solve complex engineering challenges.

Objective of the Project

• Develop analytical frameworks to identify abnormal manufacturing trends and process deviations in HBM products.
• Enable earlier detection of yield, quality, reliability, and performance excursions through data-driven methodologies.
• Apply statistical analysis, machine learning, and AI-Enabled workflows to improve manufacturing insight generation.
• Enhance engineering decision-making by transforming complex manufacturing data into meaningful and actionable information.
  

Opportunities for Full Time Employment

This internship offers exposure to semiconductor product engineering, manufacturing analytics, and Artificial Intelligence-driven engineering solutions. High-performing interns may be considered for future full-time employment opportunities, subject to business needs and hiring requirements.

Project Scope

• Analyze manufacturing, assembly, test, and characterization datasets to identify patterns and emerging process deviations.
• Develop automated data pipelines and monitoring solutions for key manufacturing and product health indicators.
• Apply statistical methods, machine learning models, and AI-Enabled analytics to detect anomalies and potential manufacturing risks.
• Investigate relationships between process parameters and critical product metrics, including yield, quality, reliability, and performance.
• Design interactive dashboards and visualization tools that provide engineering teams with actionable insights.
  

Learning Opportunities

• Gain hands-on experience with large-scale semiconductor manufacturing and product engineering datasets.
• Learn advanced data analytics, statistical modeling, and machine learning techniques in an engineering environment.
• Explore Generative AI, AI Assistants, Agentic AI, and other AI-Enabled approaches for anomaly detection and root-cause investigation.
• Develop skills in data visualization, dashboard development, and engineering communication.
• Present technical findings and recommendations to engineering stakeholders while building industry-relevant analytical expertise.
  

Deliverables

• A robust analytical solution that enables early identification of manufacturing deviations and emerging product risks.
• Automated monitoring workflows and dashboards that improve visibility into manufacturing performance indicators.
• Analytical models or methodologies that provide meaningful insight into yield, quality, reliability, or performance trends.
• A final technical presentation summarizing findings, recommendations, and measurable project outcomes.
  

Impact of the Project

• Improve the speed and effectiveness of deviation detection across HBM manufacturing processes.
• Increase visibility into key drivers affecting product yield, quality, reliability, and performance.
• Enable data-driven engineering decisions through advanced analytics and AI-Generated insights.
• Contribute to improved manufacturing efficiency and product understanding through scalable analytical solutions.
  

Skillsets Required

• Strong analytical thinking and problem-solving capabilities.
• Knowledge of statistics, data analytics, engineering principles, or machine learning concepts.
• Programming experience in Python, SQL, MATLAB, JMP, or similar analytical tools.
• Familiarity with dashboarding, data visualization, or reporting platforms.
• AI proficiency and familiarity with Artificial Intelligence tools, Generative AI, Agentic AI, or AI-Enabled workflows.
• Strong communication, collaboration, and technical presentation skills.
  

Course of Interest

The ideal candidate should be pursuing a Bachelor's or Master's degree in Electrical Engineering, Electronic Engineering, Computer Science, Data Science, Semiconductor Engineering, Physics, or a related field.

Duration of Period

The ideal candidate should be able to commit to a full-time internship period of 6 months.

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 [email protected]

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.   

Fraud alert: Micron advises job seekers to be cautious of unsolicited job offers and to verify the authenticity of any communication claiming to be from Micron by checking the official Micron careers website in the About Micron Technology, Inc.