[Summer 2027] TSMC AZ Internship Opportunities - Engineering Roles

TSMC•USA-Arizona, AZ

14h•Onsite

About The Position

TSMC Arizona engineering departments are looking for engineering talents to join our advanced technology fab, located in sunny Phoenix, Arizona. As a TSMC Intern, you will demonstrate a strong sense of reliability and enthusiasm and will possess an attitude that embodies our core values – Integrity, Commitment, Innovation and Customer Trust. This internship program offers various engineering roles including Process Integration Engineer, Yield Excellence Engineer, Process Engineer, Equipment Engineer, Intelligent Manufacturing Engineer, Advanced Material Handling System Engineer, Quality Management Engineer, Product Engineering, Mask Engineering, Central Start-Up Tool Install Engineer, Industrial Safety & Health Engineer, and Computer Integrated Manufacturing Engineer. Responsibilities vary by role but generally involve analyzing data, optimizing processes, maintaining equipment, improving systems, collaborating with teams and stakeholders, and ensuring quality and safety standards are met. Some roles may require working in a cleanroom environment and potentially lifting weights. The program is designed for interns to gain hands-on experience in semiconductor manufacturing and contribute to TSMC's advanced technology fab.

Requirements

Legally eligible to work in the United States.
Currently enrolled at an accredited university, in Bachelor, Master or Ph.D. degree in Electrical Engineering, Material Science, Chemical Engineering, Chemistry, Mechanical Engineering, Physics, Industrial Engineering, Civil Engineering, Construction or related engineering fields.
Able to work full-time for 10 weeks (40 hours per week) on-site at our Phoenix location.
Flexibility to change priorities and responsibilities to support business needs.
Self-motivated learner.
Good at proactive collaboration.
Strong communication, computer, presentation, listening, and working with others skills needed to contribute to the team and TSMC Arizona’s culture.
Ability to work in a cleanroom environment, gowning up in coveralls, hoods, boots, safety glasses and gloves.
Ability to spend significant amount of time on the factory floor working on the tools.

Nice To Haves

Knowledge of semiconductor manufacturing process and design would be a strong add.
Ability to lift weights in accordance with applicable regulations and safety guidelines, including NIOSH lifting recommendations.

Responsibilities

Analyzing Inline and EOL (End-of-Line) electrical data to determine causes for issues.
Deducing the root cause of critical issues by collaborating with respective stakeholders and innovating current techniques to combat defect issues.
Delivering robust and efficient semiconductor manufacturing through data-driven analytics and systematic problem-solving.
Optimizing processes with experimental design, precision control, and statistical methods.
Collaborating with suppliers to address technology gaps and focusing on continuous improvement in stability, quality, yield, productivity, and safety.
Improving and maintaining tool performance in a cleanroom environment to ensure quality production.
Troubleshooting alarms, installing and qualifying new tools, resolving critical equipment issues, and improving tool uptime.
Enhancing hardware capabilities, implementing systems to prevent equipment failures, and managing vendor relationships.
Ensuring the timely delivery of high-quality wafers by driving productivity and efficiency through advanced technologies.
System optimization, productivity improvement initiatives, and quality defense enhancements to support daily operations.
Focusing on automated systems that ensure efficient, timely, and accurate wafer transfers.
Improving Delivery Time Accuracy (DTA) or enhancing Stocker dispatching systems to optimize lot movement and cycle times.
Supporting TSMC's mission of world-class quality systems by collaborating with Taiwan's Central Quality team.
Monitoring wafer fabrication processes, analyzing manufacturing parameters, applying statistical methods, and leveraging predictive analytics to optimize process control.
Contributing to product success during launches and technology ramps while ensuring compliance with global quality standards.
Analyzing yield and process issues to support customer needs and drive improvements in semiconductor manufacturing.
Identifying process and quality "sweet spots" to optimize yield efficiency.
Performing detailed layout analyses to uncover root causes.
Conducting electrical and physical failure analyses to pinpoint process-stage issues.
Ensuring the performance, reliability, and efficiency of photomask tools within advanced manufacturing operations.
Collaborating with tool owners to manage the installation and maintenance of photomask equipment.
Partnering with tool vendors to improve maintenance processes.
Developing in-line monitoring systems to proactively identify and address potential issues.
Supporting the installation of manufacturing equipment and tools by conducting site assessments, preparing installation plans, and coordinating timelines.
Surveying construction sites to identify optimization opportunities.
Developing improvement proposals and presenting findings through reports or visual presentations.
Identifying bottlenecks in the installation process and recommending solutions to streamline operations.
Supporting and promoting workplace safety and environmental sustainability efforts in advanced semiconductor facilities.
Implementing safety protocols, evaluating hazards (e.g., radiation, lasers, gases, chemicals), and conducting risk assessments.
Refining high-risk SOPs to ensure a safe and compliant work environment.
Tackling analytical projects and machine vision tasks that address production line issues.
Working on projects like pattern recognition, machine learning, and web development.
Learning agile software development.
Implementing Prometheus and Grafana monitoring services.
Implementing automated deployment pipelines utilizing Microsoft Azure DevOps.
Developing machine learning/statistics models or algorithms.