- Where
- Boise, ID - ID1
- Posted
- Today
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 is expanding its semiconductor manufacturing operations in Boise through a historic $15 billion investment that will support next-generation DRAM production and advanced manufacturing capabilities. This growth creates exciting opportunities for students to contribute to the future of semiconductor technology while working in a highly collaborative, data-driven manufacturing environment.
The High Volume Manufacturing Process Engineer Intern supports process optimization, yield improvement, throughput enhancement, cost reduction, and issue resolution within a manufacturing area.
What you'd do
- Drive process optimization and manufacturing efficiency initiatives by monitoring process performance, analyzing data, and supporting area throughput and wafer output goals.
- Identify, troubleshoot, and resolve process issues that could result in yield loss, defects, equipment restrictions, excursions, or production impacts, escalating concerns when necessary.
- Apply SPC, FDC, Design of Experiments (DOE), and structured problem-solving methodologies, including 8D, to improve process capability and equipment performance.
- Partner with process owners, operations teams, and engineering stakeholders to address chronic process issues and support continuous improvement initiatives.
- Leverage Artificial Intelligence and data analytics tools, where appropriate, to identify improvement opportunities, optimize wafer processing, and enhance manufacturing performance.Minimum Qualifications
- Currently pursuing a Bachelor’s or Master’s degree in Chemical Engineering, Electrical Engineering, Materials Science, Physics, or a related engineering discipline.
- Must be actively enrolled as a student and not graduate before September 2026.
- Demonstrated understanding of Statistical Process Control (SPC) and Design of Experiments (DOE) principles.
- Proficiency in one or more technical, programming, or visualization tools such as Python, Java, MATLAB, Tableau, or Microsoft Office applications.
- Ability to analyze manufacturing or engineering data and make informed, data-driven decisions.Preferred Qualifications
- Starts
- 2026-09-23