Intern - NAND Device Engineering 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 Singapore Department NAND Device Engineering Project Title AI-Enabled Device Characterization Automation and Intelligent Engineering Workflow Platform Project Description As an AI / Data Science Intern in the NAND Device Engineering organization, you will participate in the development of AI-Enabled solutions that enhance engineering productivity, accelerate device characterization, and improve data-driven decision-making for advanced 3D NAND technologies. This internship provides an opportunity to apply Artificial Intelligence, machine learning, data science, and automation techniques to complex semiconductor engineering datasets. The project focuses on developing intelligent automation workflows, AI-assisted analysis platforms, and Agentic AI solutions that streamline device characterization activities, automate engineering insights generation, and improve project execution efficiency. Working alongside experienced engineers, you will gain exposure to semiconductor device development, large-scale data analytics, and emerging Generative AI technologies within a manufacturing and product development environment. Objective of the Project Develop an AI-Enabled platform that automates device characterization workflows, enhances engineering data analysis, and provides intelligent decision-support capabilities to accelerate technology development and engineering learning. Opportunities for Full Time Employment High-performing candidates may be considered for future opportunities , subjected to business needs and individual performance. Project Scope • Design and develop AI-Enabled workflows for automating device characterization data collection, analysis, anomaly detection, and reporting across multiple electrical characterization datasets. • Apply machine learning, statistical modeling, and Agentic AI techniques to identify performance trends, classify device behaviors, and generate engineering insights from large-scale datasets. • Develop automated data pipelines for data extraction, cleansing, feature engineering, and integration from characterization and metrology sources. • Create interactive dashboards, visualization tools, and AI Assistant capabilities that enable engineers to explore data, retrieve knowledge, and generate summary reports more efficiently. • Evaluate the application of Generative AI, Large Language Models (LLMs), and Agentic Solutions for engineering workflow automation, project tracking, technical knowledge retrieval, and intelligent report generation. Learning Opportunities • Gain practical experience applying Artificial Intelligence and machine learning techniques to semiconductor engineering challenges. • Learn how large-scale device characterization data is used to evaluate performance, variability, and technology development objectives. • Develop expertise in data engineering, analytics, visualization, and AI-enabled decision-support systems. • Explore modern Generative AI, LLM, and Agentic AI frameworks for engineering and technical applications. • Collaborate with cross-functional engineering teams to understand technology development processes and data-driven engineering methodologies. Deliverables • AI-Enabled device characterization automation workflow. • Intelligent engineering dashboard with data visualization and insight generation capabilities. • Machine learning or Agentic AI model demonstrating automated pattern recognition and data interpretation. • Automated reporting framework for engineering summary generation and knowledge sharing. • Final project presentation, technical documentation, and reusable software assets. Impact of the Project • Improve engineering efficiency through automation of repetitive data processing activities. • Accelerate analysis of characterization results and identification of meaningful device trends. • Demonstrate the value of Artificial Intelligence and Agentic AI technologies within semiconductor engineering workflows. • Enhance accessibility of engineering knowledge through intelligent data exploration and reporting tools. • Establish scalable foundations for future AI-Enabled engineering productivity solutions. Skillsets Required • Strong programming proficiency in Python and experience developing data analysis, automation, or software solutions. • Knowledge of machine learning, deep learning, data science, or Artificial Intelligence concepts through coursework, projects, or research activities. • Familiarity with data processing libraries and frameworks such as Pandas, NumPy, Scikit-learn, TensorFlow, PyTorch, LangChain, or similar technologies. • Exposure to data visualization, dashboard development, database technologies, or workflow automation platforms is desirable. • Strong analytical thinking, problem-solving capability, communication skills, self-motivation, and interest in AI-Enabled engineering solutions. Course of Interest The ideal candidate should be pursuing a Bachelor's Degree, Master's Degree, or Ph.D. in Computer Science, Data Science, Artificial Intelligence, Statistics, Electrical Engineering, Physics, Mathematics, Computer Engineering, or a related discipline. 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 focu…