Intern

About the Role

The ID1 High Volume Manufacturing Process Engineer supports process quality, yield improvement, manufacturing efficiency, and cost reduction within a high-volume semiconductor fabrication environment. This role partners closely with equipment engineers, manufacturing teams, process owners, and operations leaders to find opportunities, resolve process issues, and optimize wafer output.

Key Responsibilities

• Monitor, analyze, and improve manufacturing processes to achieve yield, quality, throughput, and cost objectives.
• Apply SPC, FDC, Design of Experiments, and systematic problem-solving methodologies to identify and resolve process deviations and chronic issues.
• Collaborate with operations, equipment, and engineering teams to address yield loss risks, tool restrictions, defects, and output interruptions.
• Perform data analysis using engineering and visualization tools to support process optimization and increase wafer output.
• Utilize approved Artificial Intelligence and AI-Assisted analytics tools, where appropriate, to enhance process monitoring, data analysis, and continuous improvement initiatives.

Requirements & Tech Stack

• Currently pursuing a Bachelor's or Master's degree in Chemical Engineering, Electrical Engineering, Materials Science, Physics, or a related engineering field, with graduation occurring after September 2027.
• Demonstrated knowledge of Statistical Process Control (SPC) and Design of Experiments (DOE).
• Proficiency in one or more technical tools such as Python, Java, MATLAB, Tableau, or Microsoft Office applications.
• Ability to analyze technical data and make sound engineering decisions in a manufacturing environment.

Qualifications

• Strong written and verbal communication skills with the ability to collaborate across multi-functional teams.
• Experience or coursework involving data collection, data cleansing, data warehousing systems, Artificial Intelligence, or advanced analytics.
• Hands-on experience with data analytics, database queries, and data visualization techniques.
• Working knowledge of semiconductor fabrication processes, manufacturing equipment, and supporting systems.
• Demonstrated organizational, prioritization, and time-management skills in a technical or academic setting.