Intern- PIE RAM (Agentic AI)

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
North Coast, Singapore (F10N)
Department
Product Integration Engineering - Real Time Defect Analysis and Metrology (RAM)
Project Title
AI-Enabled Metrology Data Analytics for Workstation Conversion
Project Description
Advanced metrology measurement techniques are utilized in leading-edge semiconductor manufacturing processes at Micron. This project focuses on applying data analytics methods to evaluate and enhance metrology workstation conversion, with the objective of improving process efficiency and measurement capability. The intern will analyze metrology data, understand manufacturing process considerations, and develop data-driven insights to evaluate workstation conversion outcomes.
Through this project, the intern will gain exposure to AI-enabled analytical tools and data-driven problem-solving approaches that support engineering decision-making and productivity improvement. The experience provides foundational knowledge in metrology, process integration, and semiconductor manufacturing, helping to build readiness for future opportunities in metrology equipment and application engineering
Objective of the Project

• Evaluate metrology workstation conversion performance using data analytics approaches.
• Identify process capability and efficiency trade-offs associated with workstation conversion.
• Explore AI-enabled methods to enhance data analysis efficiency and insight generation.
• Contribute to successful workstation conversion through data-driven recommendations.

Opportunities for Full Time Employment
High-performing interns may be considered for future internship or entry-level engineering opportunities, subject to business needs and hiring requirements.
Project Scope

• Learn fundamental metrology measurement principles and their applications in semiconductor manufacturing.
• Partner with cross-functional engineering teams to understand workstation conversion requirements and evaluation criteria.
• Analyze metrology datasets to assess process performance and measurement capability.
• Investigate opportunities to leverage AI-assisted analytics to improve insight generation and decision-making.
• Present findings and recommendations based on data analysis outcomes.

Learning Opportunities

• Gain practical experience with advanced metrology technologies and manufacturing applications.
• Develop data analytics and problem-solving skills within a semiconductor production environment.
• Learn how engineering teams evaluate process capability, measurement performance, and conversion effectiveness.
• Build familiarity with AI-enabled analytical workflows and engineering data interpretation techniques.

Deliverables

• Complete analysis of workstation conversion performance using relevant metrology datasets.
• Provide data-driven recommendations related to process efficiency and measurement capability.
• Document key findings, methodologies, and conclusions.
• Successfully contribute to the implementation and evaluation of workstation conversion activities.

Impact of the Project

• Support informed decision-making during workstation conversion initiatives.
• Improve understanding of process performance and measurement capability considerations.
• Enhance the effectiveness of data-driven engineering evaluations.
• Contribute to productivity improvements through efficient analysis methodologies.

Skillsets Required

• Basic understanding of engineering principles, statistics, or data analysis concepts.
• Familiarity with data visualization and analytical tools is advantageous.
• Interest in semiconductor manufacturing, metrology, and process engineering.
• Exposure to AI tools or AI-enabled analytical workflows is beneficial.

Course of Interest
The ideal candidate should be pursuing Engineering or a related field of study.
Duration of Period
The ideal candidate should be able to commit to a full-time internship period of a minimum 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 [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.
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