AI Engineering Summer Intern (May-Aug '27)

Job Title: AI Engineering Summer Intern (May-Aug '27)

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

• Currently 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 [email protected].