Intern - PLN IE

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Project Title Agentic AI–Driven Intelligent Planning Ecosystem for Fab Space and Capacity Optimization

Project Description This internship project focuses on the development of an Agentic AI-enabled planning ecosystem to enhance fab space utilization, tool placement planning, and decision-making across the Planning (PLN) domain. The intern will have the opportunity to contribute to the design and evaluation of an intelligent multi-agent framework that supports planning optimization through data-driven analysis and Artificial Intelligence technologies.

The project will explore the use of Agentic AI architecture and Google SDK technologies to coordinate multiple specialized AI agents, including:

• Industrial Engineering (IE) Agent for tool demand forecasting and capacity planning

• Layout Agent for space allocation analysis and constraint evaluation

• Material and Spare Planning Agent for resource planning optimization

• Operations Modelling Agent for scenario simulation and planning insights

• Cost/Capex Agent for investment and cost optimization assessments

Through collaboration with planning stakeholders, the intern will gain exposure to AI-enabled planning methodologies, multi-agent reasoning frameworks, optimization techniques, and large-scale manufacturing planning challenges.

Objective of the Project The objective of this project is to evaluate how Agentic AI solutions can improve planning effectiveness by enabling coordinated decision-making across multiple planning domains. The project aims to identify opportunities to optimize fab capacity utilization, improve planning alignment, and enhance future-state scenario evaluation through intelligent agent collaboration.

Opportunities for Full Time Employment Successful completion of the internship may provide opportunities to be considered for future full-time roles, subject to business requirements, performance, and available openings.

Project Scope The intern will have opportunities to:

• Study existing planning workflows and data inputs across the PLN domain.

• Develop proof-of-concept Agentic AI workflows for planning optimization.

• Evaluate coordination mechanisms between multiple specialized AI agents.

• Analyze planning trade-offs involving tool demand, factory layout constraints, material requirements, operational scenarios, and capital investment considerations.

• Explore AI-Enabled approaches for generating planning recommendations and scenario-based decision support.

• Document findings, recommendations, and improvement opportunities.

Learning Opportunities The intern will gain hands-on experience in:

• Agentic AI and multi-agent system design

• Generative AI and Large Language Model (LLM) applications

• Manufacturing planning and capacity optimization methodologies

• Operations research and optimization techniques

• Data analytics and scenario modelling

• AI-enabled decision support systems

• Cross-functional collaboration within semiconductor manufacturing environments

Deliverables

• Agentic AI planning ecosystem proof-of-concept or prototype

• Multi-agent workflow design documentation

• Planning optimization analysis and scenario evaluation results

• Recommendations for space utilization, tool placement, and planning improvements

• Final project presentation summarizing findings and future enhancement opportunities

Impact of the Project This project aims to demonstrate how Agentic AI technologies can contribute to improved planning effectiveness by enabling coordinated, data-driven decision-making across multiple planning functions. The outcomes may provide insights into space optimization opportunities, planning efficiency improvements, and scalable approaches for future intelligent planning ecosystems.

Skillsets Required

• Programming experience in Python, Java, or similar languages

• Knowledge of data analytics, statistics, or optimization techniques

• Familiarity with Artificial Intelligence, Generative AI, LLMs, Agentic AI, or AI-enabled workflows

• Understanding of operations research, industrial engineering, or manufacturing systems is advantageous

• Strong analytical and problem-solving skills

• Effective communication and presentation skills

• Ability to work independently on a project-based learning assignment

Course of Interest The ideal candidate should be pursuing Computer Science, Artificial Intelligence, Data Science, Industrial Engineering, Operations Research, Manufacturing Engineering, Systems 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 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 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.

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