Micron
Staff/Senior Engineer, OCT MTE CC
Boise, ID - Main Site · Staff · Full-time · Posted Sep 21, 2026
- Experience
- 5+ years in the specified areas and activities; preferred: 7+ years in semiconductor wafer fabrication, contamination control, cleanroom operations, or advanced semiconductor manufacturing, and 7+ years developing global standards or procedures across sites.
- Education
- Bachelor's degree in Engineering or a related technical field; master's degree preferred.
About the job
Leads global contamination-control programs and standards across semiconductor manufacturing sites to reduce risk, improve yield and quality, and support capacity expansion.
What you'll do
- Develop and implement contamination prevention, monitoring, and control strategies across manufacturing sites.
- Partner with engineering and manufacturing teams to investigate contamination issues and improve yield, reliability, and product quality.
- Manage cross-site projects and use AI, analytics, and automation to improve monitoring and operational effectiveness.
What they ask for
- Bachelor's degree in Engineering or a related technical field.
- 5+ years of experience in one of the listed semiconductor engineering or operations areas, applying a listed problem-solving methodology, and improving a listed manufacturing outcome in semiconductor manufacturing.
- 5+ years leading cross-functional projects, continuous improvement initiatives, or engineering programs in wafer fabrication or semiconductor manufacturing.
- Strong written and verbal communication skills in English; willingness to travel as needed.
Nice to have
- Master's degree in Engineering or a related technical field.
- Experience with AI, machine learning, advanced analytics, or automation; global standards; contamination monitoring; or related manufacturing programs.
Tools
Failure Analysis, FMEA, 8D, SPC, Root Cause Analysis, Statistical Analysis, Artificial Intelligence (AI), machine learning
AI focus
Apply AI, advanced analytics, and automation to improve process monitoring, accelerate data-driven decisions, streamline workflows, and improve engineering effectiveness and manufacturing performance.
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