CPEE PRINCIPLE/SENIOR ENGINEER (DIFF)

The OCT CPEE Diffusion Engineer is responsible for driving process and equipment engineering excellence within the Diffusion area to achieve world-class performance in safety, quality, cost, output, and technology enablement. The engineer will work closely with Manufacturing, Process Integration, Yield Enhancement, MAE, Central Teams, and Equipment Suppliers to improve equipment capability, manufacturing efficiency, productivity, and cost effectiveness.

This role requires strong technical expertise, analytical problem-solving skills, and the ability to influence cross-functional teams to deliver sustainable business results

Key Responsibilities

Technical Excellence

• Drive Diffusion process and equipment performance improvements to support manufacturing objectives.

• Identify and implement opportunities to improve Manufacturing Availability (MA), Utilization, Throughput, WPD, and RPT.

• Lead technical investigations for equipment, process, and yield excursions using structured problem-solving methodologies.

• Develop innovative solutions to improve equipment capability, reliability, and productivity.

Productivity & Capacity Improvement

• Support Max-Out, Productivity, Everest, WPD, and Cost Reduction initiatives.

• Analyze manufacturing constraints and develop solutions to improve fab output.

• Identify and execute productivity projects that improve cycle time, throughput, and equipment effectiveness.

• Support capacity planning and bottleneck reduction activities.

Cross-Functional Collaboration

• Partner with Manufacturing, PIE, Yield, MAE, and Global Central Teams to deliver business objectives.

• Drive alignment across functional teams to implement technical solutions.

• Provide technical recommendations to leadership and stakeholders based on data-driven analysis.

Supplier Engagement

• Work with equipment suppliers to develop and deploy hardware, software, and productivity improvements.

• Drive supplier accountability to resolve technical issues and improve tool performance.

• Benchmark industry best practices and identify opportunities for competitive advantage.

Continuous Improvement

• Utilize data analytics and engineering methodologies to identify improvement opportunities.

• Support technology transfers, process conversions, and new capability implementation.

• Create standard methodologies and best practices for Diffusion operations.

• Share technical knowledge and mentor junior engineers as needed.

AI-Driven Productivity & Automation

• Leverage AI-enabled tools and advanced analytics to accelerate engineering problem solving, improve productivity, and enhance decision-making.

• Utilize Microsoft Copilot and approved enterprise AI platforms to analyze large data sets, generate insights, summarize technical information, and improve engineering efficiency.

• Apply data science, machine learning, and statistical techniques to identify manufacturing improvement opportunities and predict equipment or process performance trends.

• Partner with Digital Transformation and Manufacturing teams to develop and implement AI-driven solutions for excursion detection, predictive maintenance, capacity optimization, and operational excellence.

• Drive adoption of digital engineering best practices, automation, and AI-enabled workflows across the Diffusion organization.

• Ensure responsible use of AI by adhering to Micron's information security, data privacy, and AI governance requirements.

Minimum Qualifications

• Bachelor's degree in Engineering, Materials Science, Chemical Engineering, Physics, or related technical discipline.

• Semiconductor manufacturing, process engineering, or equipment engineering experience.

• Strong problem-solving, data analysis, and technical troubleshooting skills.

• Ability to manage multiple priorities and execute projects independently.

• Strong written and verbal communication skills.

Preferred Qualifications

• Experience in Diffusion process or equipment engineering.

• Experience with productivity improvement programs, manufacturing optimization, and capacity management.

• Knowledge of statistical analysis, DOE, SPC, and structured problem-solving methodologies.

• Experience working with semiconductor equipment suppliers.

• Proven ability to drive cross-functional technical projects from concept through implementation