Semiconductor Shift Process Engineer — AI-Driven Processes

Micron Technology

Boise (ID)

On-site

USD 120,000 - 150,000

Full time

14 days+

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Benefits offered by this job

Medical, dental and vision plans

Paid time off and holidays

Disability and paid family leave

401(k) / retirement benefits

Job summary

Micron Technology is seeking an ID1 High Volume Manufacturing Shift Process Engineer in Boise to optimize semiconductor manufacturing processes, improve yield and quality, and support throughput targets. You will collaborate with equipment engineers, shift operations, process owners, and cross-functional teams to drive improvements while ensuring safety and efficiency.

The role emphasizes applying SPC/DOE, data analytics, and AI-enabled tools to identify opportunities and implement improvements

Qualifications

Bachelor's or Master's degree in Chemical Engineering, Electrical Engineering, Materials Science, Physics, or a related engineering discipline.
Ability to work any assigned shift and rotate schedules as business needs require.
Demonstrated knowledge of SPC, DOE, and structured problem-solving methodologies.
Proficiency with programming, scripting, analytics, or visualization tools such as Python, Java, MATLAB, Tableau, or Microsoft Office applications.
Experience analyzing complex manufacturing or engineering data and making process-related decisions based on technical findings.

Responsibilities

Monitor and optimize manufacturing processes to improve yield, quality, throughput, and overall equipment effectiveness while supporting area KPIs and wafer output goals.
Analyze process performance using SPC, DOE, and other engineering methodologies to identify trends, resolve excursions, and drive systematic problem solving.
Lead issue resolution activities by identifying, escalating, and addressing process, tool, defect, yield, and output-related concerns in a timely manner.
Develop, update, and maintain operational procedures, assessor checklists, documentation, and training materials to support standardized execution and compliance.
Utilize AI-enabled analytics tools, data visualization platforms, and engineering software to identify process improvement opportunities and support data-driven decision-making.