Intern
Micron Technology
About the Role
As an ID1 High Volume Manufacturing Process Engineer Intern, you will support process optimization, yield improvement, and cost reduction within a high-volume fab environment. You will collaborate with equipment engineering, operations, and multi-functional partners while applying data-driven methodologies and Applying AI to improve wafer output, stability, and performance.
Key Responsibilities
- Analyze manufacturing data and Apply SPC, FDC, and 8D methodologies alongside AI Assisted analytics to improve yield, reduce defects, and enhance tool availability.
- Investigate process excursions and Using AI, including LLMs and Generative AI tools, to identify trends, perform root-cause analysis, and recommend corrective actions.
- Collaborate with multi-functional teams to optimize wafer processing using AI-Enabled and data-driven decision-making approaches.
- Implement process improvement projects focused on increasing wafer outs, Using AI and visualization tools to enhance process capability and efficiency.
- Maintain and update process documentation, integrating insights generated from Artificial Intelligence and standard engineering practices.
Requirements & Tech Stack
- Currently pursuing a STEM degree with an expected graduation between May–June 2027.
- Ability to work approximately 20 hours per week on-site in Boise, ID for 6–8 months (September 2026–May/June 2027 preferred).
- Foundational knowledge of Statistical Process Control (SPC) and Design of Experiments (DOE).
- Experience with programming or analytics tools (e.g., Python, MATLAB, Tableau, Java, or Microsoft Suite).
- Exposure to Using AI or Applying AI (e.g., AI Assistants, LLMs, or AI Supported analytics) for data analysis or engineering problem-solving.
Qualifications
- Strong written and verbal communication skills.
- Experience with data collection systems, data cleansing, database querying, and AI Supported data workflows.
- Hands-on experience with Generative AI, LLMs, or Agentic AI solutions in academic or project settings.
- Understanding of semiconductor fabrication processes and how AI-Enabled solutions can improve manufacturing performance.
- Proven ability to manage time, prioritize effectively, and deliver results in a fast-paced, data- and AI-driven environment.