Intern

About the Role

The High Volume Manufacturing Process Engineer Intern supports process optimization, yield improvement, throughput enhancement, cost reduction, and issue resolution within a manufacturing area. This role partners closely with equipment engineering, operations teams, process owners, and cross-functional stakeholders to improve process performance and achieve key manufacturing objectives.

Key Responsibilities

• Drive process optimization and manufacturing efficiency initiatives by monitoring process performance, analyzing data, and supporting area throughput and wafer output goals.
• Identify, troubleshoot, and resolve process issues that could result in yield loss, defects, equipment restrictions, excursions, or production impacts, escalating concerns when necessary.
• Apply SPC, FDC, Design of Experiments (DOE), and structured problem-solving methodologies, including 8D, to improve process capability and equipment performance.
• Partner with process owners, operations teams, and engineering stakeholders to address chronic process issues and support continuous improvement initiatives.
• Leverage Artificial Intelligence and data analytics tools, where appropriate, to identify improvement opportunities, optimize wafer processing, and enhance manufacturing performance.

Requirements & Tech Stack

• Currently pursuing a Bachelor’s or Master’s degree in Chemical Engineering, Electrical Engineering, Materials Science, Physics, or a related engineering discipline.
• Must be actively enrolled as a student and not graduate before September 2026.
• Demonstrated understanding of Statistical Process Control (SPC) and Design of Experiments (DOE) principles.
• Proficiency in one or more technical, programming, or visualization tools such as Python, Java, MATLAB, Tableau, or Microsoft Office applications.
• Ability to analyze manufacturing or engineering data and make informed, data-driven decisions.

Qualifications

• Strong verbal and written communication skills with the ability to collaborate across technical and operational teams.
• Experience with data collection systems, data warehousing environments, and data cleansing methodologies.
• Hands-on experience in data analytics, including database querying and interpretation of large datasets.
• Working knowledge of semiconductor fabrication processes, manufacturing equipment, or supporting fab systems.
• Demonstrated organizational, prioritization, and time-management skills, with experience Applying Artificial Intelligence or advanced analytics tools to improve operational or engineering outcomes.