Sr. Manager PEE Equipment Manager

Req. ID:

JR106754 Sr. Manager PEE Equipment Manager

Our vision is to transform how the world uses information to enrich life for all.

Micron Technology is a world leader in innovating memory and storage solutions that accelerate the transformation of information into intelligence, inspiring the world to learn, communicate and advance faster than ever.

### Job Summary

The Senior Equipment Manager is responsible for leading the Assembly Equipment Engineering organization to achieve world-class performance in safety, quality, equipment reliability, productivity, cost, and technology deployment. This role drives equipment strategy, operational excellence, capacity readiness, automation, and continuous improvement across assembly manufacturing operations.

In addition, the role will champion AI Enablement and Digital Transformation, leveraging advanced analytics, machine learning, Generative AI, predictive maintenance, and intelligent automation to improve equipment performance, engineering productivity, factory efficiency, and decision-making capabilities.

## Equipment Engineering Leadership

• Lead and develop a team of equipment managers, engineers, technicians, and specialists across assembly operations.
• Establish equipment reliability strategies to achieve manufacturing output, quality, and yield targets.
• Drive equipment uptime, OEE, MTBF, MTTR, and cost-of-ownership improvements.
• Ensure readiness and qualification of equipment for NPI, technology transfers, and product ramps.
• Develop long-term equipment roadmap aligned with manufacturing growth and technology requirements.
• Manage equipment lifecycle activities including procurement, installation, qualification, upgrades, and decommissioning.
• Partner with Operations, PDE, Quality, Manufacturing, Facilities, and Global Teams to achieve operational objectives.

## Operational Excellence

• Drive continuous improvement initiatives using Lean Manufacturing, Six Sigma, and Statistical Process Control methodologies.
• Establish robust preventive, predictive, and corrective maintenance systems.
• Lead root cause analysis and corrective action processes for equipment excursions and reliability issues.
• Optimize utilization of capital equipment to support capacity expansion and productivity goals.
• Lead benchmarking and best-practice deployment across manufacturing sites.

## AI Enablement & Digital Transformation

• Develop and execute the Assembly Equipment AI Enablement strategy aligned with factory digitalization objectives.
• Drive adoption of AI tools, Copilot technologies, advanced analytics, and intelligent automation solutions within Equipment Engineering.
• Implement AI-driven Predictive Maintenance solutions utilizing equipment sensor data, FDC, SPC, MES, and manufacturing data systems.
• Champion Equipment Intelligence platforms that enable:
• Early anomaly detection
• Predictive failure analysis
• Automated root cause identification
• Real-time equipment health monitoring
• Lead deployment of machine learning models to improve:
• Equipment reliability
• Preventive maintenance effectiveness
• Capacity prediction
• Tool utilization optimization
• Partner with Data Science, IT, Manufacturing Systems, and Engineering teams to identify high-value AI opportunities.
• Establish AI governance, responsible AI practices, and data quality standards within Equipment Engineering.
• Drive automation of engineering workflows through AI-assisted reporting, troubleshooting, documentation, knowledge management, and decision support systems.
• Build organizational capability by developing AI literacy and upskilling programs for engineers and technicians.
• Sponsor development of intelligent engineering assistants, AI agents, and automated knowledge systems supporting equipment operations.
• Measure and report AI impact using defined metrics such as:
• Productivity improvement
• Engineering man-hour avoidance
• Equipment downtime reduction
• OEE improvement
• Cost avoidance
• Reliability enhancement

## Technology & Innovation Leadership

• Evaluate and deploy emerging manufacturing technologies, Industry 4.0 solutions, and smart manufacturing systems.
• Lead technology scouting for next-generation equipment monitoring and automation platforms.
• Drive integration of IoT, Digital Twin, AI, and advanced process control solutions into manufacturing operations.
• Foster a culture of innovation and continuous learning.

## Talent Development

• Build a high-performing engineering organization through coaching, mentoring, and succession planning.
• Establish technical competency frameworks for equipment engineering teams.
• Promote AI competency development, data-driven decision making, and digital engineering skills.
• Drive organizational engagement and leadership development.

## Quality, Safety & Compliance

• Ensure compliance with all safety, environmental, quality, and corporate governance requirements.
• Champion a safety-first culture.
• Ensure equipment systems meet reliability, regulatory, and manufacturing standards.
• Support audit readiness and compliance activities.

# Qualifications

### Education

• Bachelor's Degree in Mechanical Engineering, Electrical Engineering, Electronics Engineering, Mechatronics, Manufacturing Engineering, or related discipline.
• Master's Degree preferred.

### Experience

• 12+ years of semiconductor manufacturing experience.
• 5+ years of leadership experience managing equipment engineering organizations.
• Strong experience in assembly manufacturing equipment and automation systems.
• Proven track record leading large engineering teams and factory-wide initiatives.

### Preferred Experience

• AI/ML deployment in manufacturing environments.
• Smart Factory, Industry 4.0, Digital Twin, Predictive Maintenance, or Data Analytics programs.
• Semiconductor Assembly, Packaging, Test, or Backend Manufacturing operations.
• Experience with MES, FDC, SPC, APC, and Manufacturing Intelligence platforms.

#

# Key Competencies

### Leadership

• Strategic Thinking
• Change Leadership
• Organizational Development
• Stakeholder Management

### Technical

• Equipment Reliability Engineering
• Semiconductor Manufacturing
• Predictive Maintenance
• Data Analytics
• Statistical Analysis
• Manufacturing Automation

### Digital & AI

• AI Strategy & Enablement
• Generative AI Applications
• Machine Learning Fundamentals
• Manufacturing Data Systems
• Digital Transformation Leadership
• Intelligent Automation

### Business

• Cost Management
• Capacity Planning
• Operational Excellence
• Continuous Improvement
• Risk Management

### Success Metrics (First-Year Expectations)

• ≥5% improvement in Equipment OEE
• ≥15% reduction in unplanned downtime
• ≥20% increase in predictive maintenance coverage
• Deployment of AI-enabled equipment intelligence capability across critical assembly toolsets
• AI adoption by >80% of Equipment Engineering organization
• Demonstrated engineering productivity gains through AI automation initiatives

Job Profile(s):

Manufacturing Process Engineer Manager 2

Relocation level: (TBD)

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As a world leader in the semiconductor industry, Micron is dedicated to your personal wellbeing and professional growth. Micron benefits are designed to help you stay well, provide peace of mind and help you prepare for the future. We offer a choice of medical, dental and vision plans in all locations enabling team members to select the plans that best meet their family healthcare needs and budget. Micron also provides benefit programs that help protect your income if you are unable to work due to illness or injury, and paid family leave. Additionally, Micron benefits include a robust paid time-off program and paid holidays. For additional information regarding the Benefit programs available, please see the Benefits Guide posted on Benefits | Micron Technology, Inc

Micron is proud to be an equal opportunity workplace and is an affirmative action employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, age, national origin, disability, protected veteran status, gender identity or any other factor protected by applicable federal, state, or local laws.