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Fab Equipment Engineering Intern
Job Location:
Job Location:
Durham, NC - USA
Monthly Salary:
Not provided by the employer
Monthly Salary:
Posted:
3 October 2026 (3 days ago)
Posted:
Application Deadline:
31 December 2026
Application Deadline:
Vacancies:
1 Vacancy
Vacancies:
Job Summary
MACOM (NASDAQ: MTSI) is a global leader in the design and manufacture of advanced semiconductor products across a diverse range of end markets including Data Centers Telecommunications Industrial and Aerospace and Defense. We develop innovative cutting-edge technologies and products across the spectrum of radio frequency (RF) microwave millimeter wave photonics and high-speed analog technologies. Our solutions support critical network infrastructure applications like artificial intelligence high performance computing satellite communications radar unmanned aerial vehicles medical equipment test and measurement and advanced wireless networks.
MACOM has more than 75 years of expertise in semiconductor process development wafer fabrication circuit design advanced packaging systems architecture and applications engineering. We are committed to our customers success. We partner with customers to help solve their most challenging problems by providing semiconductor solutions that are at the forefront of the highest power highest frequency and/or highest data rates.
Leading technologies innovative products and driven employees. Come be a part of MACOM and help advance the next generation of connectivity infrastructure!
Equipment Engineering & Manufacturing Analytics Intern (Summer)
At our Durham NC wafer fabrication facility interns gain hands-on experience supporting advanced semiconductor manufacturing equipment while contributing to real engineering projects that impact production reliability and factory performance.
Position Summary
MACOM is seeking a highly motivated Engineering Intern to support the Equipment Engineering organization within our semiconductor wafer fabrication facility.
This internship is designed around a real-world engineering challenge: developing a strategy to collect and analyze operational data from legacy semiconductor manufacturing equipment that does not currently support modern factory automation interfaces such as SECS/GEM.
The intern will work alongside Equipment Engineers Technicians Manufacturing personnel and Automation teams to evaluate existing equipment data sources develop methods for automated data collection and create analytics tools capable of improving equipment visibility and decision making.
This position provides hands-on exposure to semiconductor manufacturing equipment equipment reliability engineering manufacturing analytics factory automation and artificial intelligence applications in a production environment.
Primary Internship Project
AI-Enabled Legacy Equipment Data Integration
Many semiconductor tools within manufacturing environments generate valuable operational information but lack standardized communication interfaces capable of automatically sharing data with factory systems.
The intern will be tasked with investigating and developing a framework to:
Identify available run history and operational data sources from legacy equipment.
Evaluate methods of capturing equipment activity data.
Design an intermediate data structure capable of standardizing information from multiple equipment platforms.
Develop automated methods for collecting organizing and analyzing equipment activity.
Utilize AI and analytics tools to classify equipment operating states downtime events and utilization trends.
Create dashboard visualizations and reports that improve visibility to tool performance.
Responsibilities
Equipment Engineering Support
Assist Equipment Engineers with monitoring equipment performance and reliability metrics.
Participate in equipment troubleshooting activities and root cause investigations.
Support preventive maintenance and equipment improvement initiatives.
Assist with engineering documentation and procedure updates.
Support equipment installation qualification and upgrade activities as opportunities arise.
Manufacturing Analytics Project
Investigate potential sources of run log and operational data from manufacturing equipment.
Develop methods to collect and organize equipment activity information.
Create databases dashboards and reporting tools that summarize equipment utilization and performance.
Analyze data trends and develop recommendations for future factory digitalization initiatives.
Present project updates and findings to engineering leadership throughout the internship.
Expected Deliverables
By the conclusion of the internship the selected candidate should provide:
Assessment of legacy manufacturing equipment data sources.
Proposed framework for equipment data collection and standardization.
Proof-of-concept analytics dashboard.
AI-assisted equipment utilization or event classification model.
Final presentation summarizing results recommendations and future opportunities.
Required Qualifications
Currently pursuing a Bachelors degree in:
o Mechanical Engineering
o Electrical Engineering
o Industrial Engineering
o Manufacturing Engineering
o Computer Engineering
o Computer Science
o Data Science
o Related Engineering or Technical Discipline
Must be actively enrolled in an accredited university and returning to school after completion of the internship.
Strong analytical and problem-solving skills.
Excellent verbal and written communication skills.
Ability to work independently and collaboratively within a technical team.
Proficiency with Microsoft Excel Word and PowerPoint.
Preferred Qualifications
Experience with Python SQL Power BI Tableau or other data analytics tools.
Experience with AI machine learning or data science coursework.
Coursework related to controls systems automation manufacturing systems databases or software development.
Previous internship laboratory research or technical project experience.
Interest in semiconductor manufacturing equipment engineering and factory automation.
What Youll Learn
Semiconductor manufacturing operations
Equipment reliability engineering
Factory automation concepts
Manufacturing analytics
Artificial intelligence applications in manufacturing
Root cause analysis
Engineering project management
Cross-functional collaboration within a high-volume semiconductor fab
Physical Requirements
Ability to work within a semiconductor cleanroom environment while wearing required personal protective equipment.
Occasional lifting up to 50 pounds.
Ability to sit stand bend and walk for extended periods within a manufacturing environment.
During the 12 weeks each Intern will:
Be given an individual and well-defined project with set outcome goals
Gain hands on experience
Receive excellent training and ongoing supervision
Be invited to attend an intern webinar series
Attend networking/social events
Attend and present at Poster Session about each Interns project successes and pitfalls
Receive formal written feedback
EEO:
MACOM is an Equal Opportunity Employer committed to a diverse workforce. MACOM will not discriminate against any worker or job applicant on the basis of race color religion sex gender identity sexual orientation national origin age disability genetic information veteran status military service marital status or any other category protected under applicable law.
Reasonable Accommodation:
MACOM is committed to working with and providing reasonable accommodations to qualified individuals with physical and mental disabilities. If you have a disability and are in need of a reasonable accommodation with respect to any part of the application process please call 1- or email Provide your name phone number and the position title and location in which you are interested and nature of accommodation needed and we will get back to you. We also work with current employees who request or need reasonable accommodation in order to perform the essential functions of their jobs.
Required Experience:
Intern
About Company
MACOM designs and manufactures high-performance semiconductor products for the Telecommunications, Industrial and Defense, and Data Center industries.
