ATE Process Engineer ID1

About the Role

As a High Volume Manufacturing Shift Process Engineer, you will be responsible for improving process quality, yield, equipment performance, and manufacturing efficiency within your assigned area. You will analyze process performance, resolve manufacturing challenges, and drive continuous improvement initiatives that support area objectives and semiconductor production goals. In this role, you will partner closely with equipment engineers, shift operations leaders, and cross-functional stakeholders to identify opportunities, implement solutions, and optimize wafer output. Your contributions will directly support Micron's advanced memory manufacturing capabilities that enable next-generation AI and data-intensive applications.

Key Responsibilities

• Complete all required safety training and perform work in accordance with Micron safety policies and procedures.
• Monitor process performance and respond to yield, defect, quality, and equipment-related issues to maintain manufacturing stability.
• Apply SPC, FDC, DOE, and structured problem-solving methodologies to improve process capability and operational performance.
• Analyze manufacturing and engineering data to identify trends, drive corrective actions, and support process decisions.
• Partner with operations, equipment engineering, and process teams to achieve throughput, quality, and wafer output goals.
• Lead and support projects focused on process optimization, productivity improvements, and cost reduction initiatives.
• Develop, maintain, and improve process documentation, reaction plans, procedures, and training materials.
• Escalate critical process issues and drive timely resolution to minimize manufacturing impact.

Requirements & Tech Stack

• Degree in Chemical Engineering, Mechanical Engineering, Electrical Engineering, Materials Science, Physics, or a related engineering field.
• Experience applying AI, machine learning, or advanced data analytics through coursework, research, internships, or industry experience.
• Working knowledge of Statistical Process Control (SPC) and Design of Experiments (DOE).
• Proficiency with one or more technical tools such as Python, Java, MATLAB, Tableau, or Microsoft Office applications.
• Strong analytical, troubleshooting, problem-solving, and communication skills.

Preferred Qualifications

• Experience with semiconductor manufacturing processes, process development, equipment engineering, or manufacturing data analysis through industry, laboratory, or academic research environments.
• Knowledge of data collection systems, data warehousing, and data cleansing methodologies.
• Understanding of semiconductor fabrication processes, equipment, and supporting systems.
• Demonstrated ability to manage competing priorities and collaborate effectively in a fast-paced manufacturing environment.
• Experience and/or interest in developing Agentic AI workflows into current or future processes.