[Summer 2027] TSMC AZ Internship Opportunities - Engineering Roles 1

TSMC•Phoenix, AZ

4d•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.

Requirements

Must be legally eligible to work in the United States
Must be 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.
Must be able to work full-time for 10 weeks (40 hours per week) on-site at our Phoenix location from: Semester system: June 1, 2026 to August 7, 2026 OR Quarter system: June 22, 2026 to August 28, 2026
Knowledge of semiconductor manufacturing process and design would be a strong add.
Flexibility to change priorities and responsibilities to support business needs
The candidate will be expected to be self-motivated learner, good at proactive collaboration, and should get the opportunity to work in a team presenting and discussion their work and ideas.
Strong communication, computer, presentation, listening, working with others needed to contribute to the team and TSMC Arizona’s culture.

Nice To Haves

Some roles may require the ability to: (a) Lift weights in accordance with applicable regulations and safety guidelines, including NIOSH lifting recommendations. (b) Able to work in a cleanroom environment, gowning up in coveralls, hoods, boots, safety glasses and gloves. Spend significant amount of time on the factory floor working on the tools

Responsibilities

Focus on analyzing Inline and EOL (End-of-Line) electrical data to determine causes for issues, in collaboration with Integration, YED (Yield Excellence Department), and Process/Equipment engineers.
Focus on defect inspection methodology to effectively deduce the root cause of critical issues by collaborating with respective stakeholders and innovate the current techniques to combat defect issues live on the production line.
Focus on delivering robust and efficient semiconductor manufacturing through data-driven analytics and systematic problem-solving. Optimize processes with experimental design, precision control, and statistical methods. Collaborate with suppliers to address technology gaps and focus on continuous improvement in stability, quality, yield, productivity, and safety.
Focus on improving and maintaining tool performance in a cleanroom environment to ensure quality production. Key duties include troubleshooting alarms, installing and qualifying new tools, resolving critical equipment issues, and improving tool uptime. Additionally, the role involves enhancing hardware capabilities, implementing systems to prevent equipment failures, and managing vendor relationships while coordinating with facilities, vendors, and manufacturing teams.
Focus on ensuring the timely delivery of high-quality wafers by driving productivity and efficiency through advanced technologies such as Smart Scheduling and Precise Dispatching. Responsibilities include system optimization, productivity improvement initiatives, and quality defense enhancements to support daily operations.
Focus on automated systems that ensure efficient, timely, and accurate wafer transfers. Projects may include improving Delivery Time Accuracy (DTA) or enhancing Stocker dispatching systems to optimize lot movement and cycle times.
Support on TSMC's mission of world-class quality systems by collaborating with Taiwan's Central Quality team. Your role includes monitoring wafer fabrication processes, analyzing manufacturing parameters, applying statistical methods, and leveraging predictive analytics to optimize process control. You'll also contribute to product success during launches and technology ramps while ensuring compliance with global quality standards.
Focus on analyzing yield and process issues to support customer needs and drive improvements in semiconductor manufacturing. Your work will involve identifying process and quality "sweet spots" to optimize yield efficiency, performing detailed layout analyses to uncover root causes, and conducting electrical and physical failure analyses to pinpoint process-stage issues.
Be responsible for ensuring the performance, reliability, and efficiency of photomask tools within our advanced manufacturing operations. This role involves collaborating with tool owners to manage the installation and maintenance of photomask equipment, partnering with tool vendors to improve maintenance processes, and developing in-line monitoring systems to proactively identify and address potential issues.
Focus on supporting the installation of manufacturing equipment and tools by conducting site assessments, preparing installation plans, and coordinating timelines with internal teams. You will work on projects such as surveying construction sites to identify optimization opportunities, developing improvement proposals, and presenting findings through reports or visual presentations. Demonstrate project management skills by identifying bottlenecks in the installation process and recommending solutions to streamline operations.
Focus on supporting and promoting workplace safety and environmental sustainability efforts in advanced semiconductor facilities. Collaborate with departments to implement safety protocols, evaluate hazards (e.g., radiation, lasers, gases, chemicals), conduct risk assessments, and refine high-risk SOPs to ensure a safe and compliant work environment.
Be part of TSMC's DevOps team to tackle analytical projects and machine vision tasks that address production line issues. Work on projects like pattern recognition, machine learning, and web development while learning agile software development, implement Prometheus and Grafana monitoring services that were deployed to Kubernetes platform, implemented automated deployment pipelines utilizing Microsoft Azure DevOps and machine learning/statistics model or algorithms developed.