AI Engineering Summer Intern (May-Aug '27)

If you are looking for a challenging and exciting career in the world of technology, then look no further. Skyworks is an innovator of high-performance analog semiconductors whose solutions are powering the wireless networking revolution. Through our broad technology expertise and one of the most extensive product portfolios in the industry, we are Connecting Everyone and Everything, All the Time.

At Skyworks, you will find a fast-paced environment with a strong focus on global collaboration, minimal layers of management, and the freedom to make meaningful contributions in a setting that encourages creative thinking. We are excited about the opportunity to work with you and glad you want to be part of a team of talented individuals who together are changing the way the world communicates.

Requisition ID: 78595 

Description

We are seeking a highly motivated AI Engineering Intern to support the development of advanced analytics and machine learning solutions for semiconductor manufacturing equipment. The intern will work closely with Manufacturing Engineers, Equipment Engineers, Industrial Engineers, and Operations teams to leverage equipment data, fault logs, sensor information, and maintenance records to identify predictive and preventative maintenance opportunities within a high-volume semiconductor fabrication environment. 

This role offers a unique opportunity to apply Artificial Intelligence (AI), Machine Learning (ML), and Data Analytics techniques to real-world manufacturing challenges, helping improve equipment uptime, yield, reliability, and operational efficiency. 

Learning Opportunities 

During the internship, you will gain hands-on experience with: 

Semiconductor wafer fabrication operations 

Advanced manufacturing systems 

Industrial AI and machine learning applications 

Equipment reliability engineering 

Predictive maintenance methodologies 

Data engineering and analytics platforms 

Real-world deployment of AI models in production environments 

Success Metrics 

By the end of the internship, the candidate is expected to: 

Develop a proof-of-concept predictive maintenance model. 

Identify key drivers of equipment downtime. 

Demonstrate measurable prediction accuracy for selected failure modes. 

Deliver dashboards and actionable insights to engineering teams. 

Present project outcomes and future recommendations to fab leadership. 

Duration of Internship: May -August 2027

Responsibilities

Analyze large volumes of equipment and manufacturing data from semiconductor production tools.

Develop machine learning models to identify patterns that may indicate impending equipment failures or process degradation.

Create predictive maintenance algorithms using historical maintenance records, fault logs, alarms, sensor data, and process metrics.

Evaluate equipment health indicators and recommend preventative maintenance actions.

Develop dashboards and visualizations that communicate equipment performance and risk trends.

Collaborate with equipment engineers to validate model predictions against actual tool performance.

Investigate root causes of recurring equipment failures and identify opportunities for proactive intervention.

Assist in building automated monitoring systems for critical manufacturing assets.

Conduct statistical analysis of maintenance effectiveness and equipment reliability metrics.

Present findings and recommendations to engineering and operations leadership. 

Desired Project Areas The intern may contribute to one or more of the following initiatives: 

Predictive Maintenance 

Forecast equipment failures before they occur. 

Identify early warning indicators from sensor and equipment telemetry data. 

Develop Remaining Useful Life (RUL) estimation models. 

Fault Detection & Classification 

Build anomaly detection models for equipment health monitoring. 

Classify equipment alarms and fault signatures. 

Detect abnormal operating conditions in real time. 

Preventative Maintenance Optimization 

Recommend maintenance intervals based on actual equipment condition. 

Reduce unnecessary preventative maintenance activities. 

Improve maintenance scheduling to minimize production impact. 

Equipment Reliability Analytics 

Analyze Mean Time Between Failure (MTBF). 

Analyze Mean Time To Repair (MTTR). 

Identify chronic tool reliability issues and improvement opportunities. 

Required Experience and Skills

urrently pursuing a BS, MS, or PhD in: 

Computer Science 

Data Science 

Artificial Intelligence 

Electrical Engineering 

Mechanical Engineering 

Industrial Engineering 

Computer Engineering 

Related technical discipline 

Experience with one or more programming languages: 

Python 

R 

MATLAB 

Knowledge of: 

Machine Learning fundamentals 

Statistical data analysis 

Data visualization techniques 

SQL or database querying 

Strong analytical and problem-solving skills. 

Ability to work effectively in a cross-functional engineering environment. 

Desired Experience and Skills

The typical pay range for an Engineering intern across the U.S. is currently USD $29.00 - $49.00 per hour and for a Non-Engineering intern across the U.S. is currently USD $23.00 - $42.00 per hour. Starting pay will depend on level of education, the ultimate job duties and requirements, and work location. Skyworks has different pay ranges for different work locations in the U.S.

Skyworks is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, age, sex, sexual orientation, gender identity, national origin, disability, protected veteran status, or any other characteristic protected by law. Skyworks strives to create an accessible workplace; if you need an accommodation due to a disability, please contact us at View email address on us.fitly.work.