Micron
Senior Manager, Wet Process Equipment Engineering
Boise, ID - Main Site · Manager · Full-time · Posted Oct 13, 2026
- Experience
- 10+ years of semiconductor manufacturing experience and 5+ years of leadership experience.
- Education
- Bachelor’s degree or higher in Engineering, Chemical Engineering, Materials Science, Physics, Chemistry, or a related technical field.
About the job
Leads Micron’s wet process equipment engineering organization and strategy to improve equipment reliability and high-volume semiconductor manufacturing performance.
What you'll do
- Lead and develop engineering leaders, equipment engineers, and technical experts.
- Own wet process equipment strategy and improve reliability, availability, throughput, quality, cost, and maintenance performance.
- Partner across engineering, manufacturing, facilities, suppliers, and global teams on technology introductions, factory output, capacity plans, and capital projects.
What they ask for
- Bachelor’s degree or higher in Engineering, Chemical Engineering, Materials Science, Physics, Chemistry, or a related technical field.
- 10+ years of semiconductor manufacturing experience, including equipment engineering, reliability, maintenance strategy, and performance optimization.
- 5+ years of leadership experience managing engineering teams, technical organizations, or engineering managers.
- Demonstrated success leading complex cross-functional technical initiatives and delivering measurable operational improvements in high-volume manufacturing.
Nice to have
- Experience with wet processing equipment, chemical delivery systems, contamination control, or defectivity reduction.
- Experience with 300mm manufacturing, factory ramp, predictive maintenance, advanced process control, Lean Manufacturing, Six Sigma, or AI-enabled analytics.
Tools
AI-assisted analytics, advanced analytics, automation, digital manufacturing solutions, advanced process control, Lean Manufacturing, Six Sigma
AI focus
Preferred experience using AI-assisted analytics and AI-enabled tools for data interpretation, anomaly detection, yield improvement, equipment performance, operational effectiveness, and engineering productivity.
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