Shift Process Engineer – AI-Driven Packaging & Yield

Micron Technology, Inc; Boise, Northern (ID, KY); Hybrid; USD 90,000 - 125,000; Full time

Job summary

Micron Technology, Inc. in Boise, Idaho, seeks a Shift Process Engineer for Advanced Packaging Technology Development to support and improve assembly processes in a fast-paced development environment.

You will analyze process data to drive decisions, identify issues with FMEA/8D/SPC methodologies, and collaborate across engineering, operations, suppliers, and global sites to boost yield, quality, and equipment effectiveness while evaluating AI-enabled changes and vendor solutions.

Qualifications

• Bachelor’s degree in a technical field (engineering, materials science, physics or chemistry).
• Experience analyzing data to drive process improvements.
• Knowledge of SPC principles and process control methodologies.
• Ability to communicate technical information to diverse audiences.
• Experience using AI-enabled tools such as Copilot, Claude, Gemini, or similar.

Responsibilities

• Identify, diagnose, and resolve process issues using FA, 8D, SPC, and FDC methods.
• Analyze process and manufacturing data to improve yield and quality.
• Collaborate with engineering, operations, suppliers, and global sites to optimize performance.
• Monitor trends and implement improvements to increase process capability and equipment effectiveness.
• Support evaluation and qualification of AI-enabled process changes, materials, and vendor solutions.

Skills

Data analysis

Process improvements

Cross-functional collaboration

Effective communication

AI-enabled tools

Education

Bachelor’s degree in Engineering, Materials Science, Physics, Chemistry, or related field

Tools

Microsoft Office

Data analysis tools

Job description

Micron Technology, Inc. in Boise, Idaho, seeks a Shift Process Engineer for Advanced Packaging Technology Development to support and improve assembly processes in a fast-paced development environment.

You will analyze process data to drive decisions, identify issues with FMEA/8D/SPC methodologies, and collaborate across engineering, operations, suppliers, and global sites to boost yield, quality, and equipment effectiveness while evaluating AI-enabled changes and vendor solutions.