Process Engineer Intern

About Micron

Micron Technology is a global leader in memory and storage innovation, transforming how the world uses information to enrich life for all. The Boise site is at the center of a historic semiconductor manufacturing expansion, supported by a $15 billion investment. This growth creates opportunities for students to contribute to leading-edge DRAM manufacturing while developing technical expertise in one of the world's most advanced fabrication environments.

Role Overview

The ID1 High Volume Manufacturing Process Engineer supports process quality, yield improvement, manufacturing efficiency, and cost reduction within a high-volume semiconductor fabrication environment. This role partners with equipment engineers, manufacturing teams, process owners, and operations leaders to identify opportunities, resolve process issues, and optimize wafer output.

The successful candidate will apply statistical analysis, engineering principles, and data-driven decision making to improve manufacturing performance, support operational excellence, and contribute to key area performance indicators.

Responsibilities

• Monitor, analyze, and improve manufacturing processes to achieve yield, quality, throughput, and cost objectives.
• Apply SPC, FDC, Design of Experiments, and systematic problem-solving methodologies to identify and resolve process deviations and chronic issues.
• Collaborate with operations, equipment, and engineering teams to address yield loss risks, tool restrictions, defects, and output interruptions.
• Perform data analysis using engineering and visualization tools to support process optimization and increase wafer output.
• Utilize approved Artificial Intelligence and AI-Assisted analytics tools, where appropriate, to enhance process monitoring, data analysis, and continuous improvement initiatives.

Minimum Qualifications

• Currently pursuing a Bachelor's or Master's degree in Chemical Engineering, Electrical Engineering, Materials Science, Physics, or a related engineering field, with graduation occurring after September 2027.
• Demonstrated knowledge of Statistical Process Control (SPC) and Design of Experiments (DOE).
• Proficiency in one or more technical tools such as Python, Java, MATLAB, Tableau, or Microsoft Office applications.
• Ability to analyze technical data and make sound engineering decisions in a manufacturing environment.

Preferred Qualifications

• Strong written and verbal communication skills with the ability to collaborate across multi-functional teams.
• Experience or coursework involving data collection, data cleansing, data warehousing systems, Artificial Intelligence, or advanced analytics.
• Hands-on experience with data analytics, database queries, and data visualization techniques.
• Working knowledge of semiconductor fabrication processes, manufacturing equipment, and supporting systems.
• Demonstrated organizational, prioritization, and time-management skills in a technical or academic setting.