The board
Micron- Hours
- Full time
- Where
- Boise, ID - Main Site
- Posted
- 4 days ago
Our vision is to transform how the world uses information to enrich life for all.
Micron Technology is a world leader in innovating memory and storage solutions that accelerate the transformation of information into intelligence, inspiring the world to learn, communicate and advance faster than ever.
Micron’s Boise site is undergoing a historic $15 billion investment in advanced semiconductor manufacturing, with DRAM production planned for the second half of the decade. As part of Micron’s broader $150 billion global expansion, the High Volume Manufacturing (HVM) organization leverages AI-Enabled innovation, advanced analytics, and operational excellence to deliver world-class memory solutions at scale.
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.
What you'd do
- 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.Minimum Qualifications
- 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.Preferred Qualifications
- Starts
- 2026-10-01