About the role
AI summarisedThis is an internship role at Micron Technology, a semiconductor company, focused on machine learning and AI engineering within product engineering. The intern will work on building predictive models for yield and reliability, developing AI agents for automation, and handling semiconductor datasets. The role is suitable for students pursuing degrees in computer science, electrical engineering, or data science with basic Python and ML knowledge.
IDMFull-timeSTPG
Key Responsibilities
- Assist in building predictive models for yield, reliability, and test‑time optimization using structured/tabular data.
- Explore ML techniques (regression, tree‑based models, boosting algorithms) to extract insights from probe, wafer, and manufacturing datasets.
- Support model evaluation, validation, and feature engineering workflows.
- Help develop AI agents that automate engineering tasks such as report generation, data processing, anomaly detection, or test program checks.
- Learn how agents interact with enterprise tools (e.g., JIRA, Confluence, SharePoint) and engineering platforms.
- Participate in data cleaning, transformation, and structuring of high‑volume semiconductor datasets.
- Work with cross‑functional teams to understand data sources and how they feed into ML/AI pipelines.
- Identify potential areas where AI can improve test efficiency, yield, or engineering productivity.
- Contribute to internal prototypes, demos, and best‑practice documentation.
- Work with senior engineers and CDS mentors to learn how AI knowledge is transferred within Product Engineering.
- Participate in training sessions, bootcamps, or hands‑on CDS learning exercises.
Requirements
- Pursuing a Bachelor's or Master's degree in: Computer Science, Electrical/Electronic Engineering, Data Science / Analytics, or related technical field.
- Basic Python knowledge (Pandas, NumPy, Scikit‑learn).
- Familiarity with ML concepts for structured data (regression, decision trees, feature engineering).
- Interest in AI agents, LLMs, or workflow automation.
- Experience with TensorFlow/PyTorch for image/text/log data (nice-to-have).
- Awareness of agentic AI frameworks (LangChain, Copilot Studio) (nice-to-have).
- Understanding of MLOps concepts (model lifecycle, deployment) (nice-to-have).
- Interest in cloud AI (Azure, AWS) (nice-to-have).
- Prior coursework or projects in ML, data engineering, or automation (nice-to-have).
- Curiosity and willingness to learn.
- Strong analytical thinking.
- Good communication and comfort working with engineering teams.