Drimva

Micron

New College Grad - Manufacturing Development Engineering (MDE) Shift Engineer

Boise, ID - Main Site · Entry level · Full-time · Posted Oct 30, 2026

Experience
No specific number of years stated; Bachelor of Science applicants need proven experience in Semiconductor Manufacturing or Process Development.
Education
Master's degree in a stated or related engineering field, or Bachelor of Science with proven experience in Semiconductor Manufacturing or Process Development.

About the job

Serve as the off-shift engineering decision-maker for 24/7 development of next-generation DRAM processes, troubleshooting issues and supporting development execution.

What you'll do

  • Make real-time decisions on development wafers, tools, process deviations, and execution risks.
  • Partner with development, integration, equipment, manufacturing, and shift teams to troubleshoot and sustain development activities.
  • Use data and fault-detection systems to investigate excursions, improve process performance, and support qualifications and continuous improvement.

What they ask for

  • Master's degree in Chemical Engineering, Electrical Engineering, Materials Science, Physics, or a related engineering field, or a Bachelor of Science with proven experience in Semiconductor Manufacturing or Process Development.
  • Ability to work a 12-hour rotating shift schedule, including nights, weekends, and holidays.
  • Solid understanding of semiconductor manufacturing, process control, and engineering problem-solving.
  • Understanding of SPC, DOE, E3 FD, and data-driven decision-making; proficiency with Microsoft Office applications.

Nice to have

  • Experience in area-specific process development, Manufacturing Development Engineering, and/or High-Volume Manufacturing.
  • Experience with equipment troubleshooting, analytics, AI-enabled engineering solutions, or LLMs.

Tools

SPC, DOE, E3 FD, Microsoft Office, Excel, PowerPoint, Word, LLMs

AI focus

Use data analytics and AI-enabled tools to improve decision quality and operational productivity; preferred experience includes applying LLMs to workflow efficiency, data analysis, or engineering decisions.

Model-written summary · the original posting is authoritative

First seen Oct 31, 2026 · Last verified Nov 5, 2026 (UTC)