We believe power is a promise - a shared commitment to be there for others when it matters most.

For more than 65 years, we've turned big ideas into solutions that help protect homes, strengthen businesses and build a more resilient, efficient, sustainable energy future.

Ready to Power a Smarter World with us?

Position Overview

Generac is seeking a highly motivated Master's-level Engineering Intern to join the AI Solutions team supporting Corporate Operations and Supply Chain. This internship offers the opportunity to work at the intersection of artificial intelligence, advanced analytics, manufacturing operations, and supply chain optimization.

You will partner with business leaders, data scientists, engineers, and operational stakeholders to identify opportunities where AI, machine learning, automation, and digital technologies can improve efficiency, decision-making, quality, and customer outcomes. The role provides hands-on experience developing and evaluating innovative solutions that support digital transformation and operational excellence.

This position is required to work on site at our corporate headquarters in Waukesha, WI during scheduled work hours,

Essential Duties

Support the development, testing, and implementation of AI-enabled solutions for manufacturing, supply chain, quality, and corporate operations.

Analyze operational and supply chain data to identify trends, inefficiencies, and opportunities for automation or process improvement.

Assist in building data models, dashboards, predictive analytics, and decision-support tools using enterprise data.

Collaborate with cross-functional stakeholders to gather business requirements and translate operational challenges into analytical solutions.

Contribute to pilot projects involving machine learning, generative AI, optimization algorithms, process automation, and intelligent workflows.

Research emerging AI technologies and industry practices relevant to manufacturing and supply chain environments.

Prepare clear presentations and recommendations that summarize findings, potential business value, and implementation considerations.

Document methodologies, results, and lessons learned to help scale successful solutions across the enterprise.

Potential Project Areas

•  Supply and demand planning optimization

•  Supplier collaboration and procurement analytics

•  Inventory forecasting and replenishment modeling

•  Quality improvement through AI-driven insights

•  Manufacturing process automation

•  Generative AI for operational productivity

•  Predictive maintenance analytics

•  Advanced reporting and business intelligence

Education

Currently pursuing master's degree in Industrial Engineering, Manufacturing Engineering, Systems Engineering, Mechanical Engineering, Data Science, Operations Research, Supply Chain Analytics, Computer Engineering, or a related discipline.

Knowledge, Skills & Abilities

Strong analytical, quantitative, and problem-solving skills.

Experience with statistical analysis, quantitative modeling, or data analysis.

Advanced proficiency in Microsoft Excel.

Strong written and verbal communication skills, with the ability to explain technical concepts to varied audiences.

Ability to work independently while collaborating effectively across functions.

Preferred Qualifications

Experience with Python, R, SQL, or a similar programming language.

Exposure to machine learning, artificial intelligence, predictive analytics, or optimization.

Familiarity with manufacturing, supply chain, or operations environments.

Experience with Power BI, Tableau, or another visualization platform.

Knowledge of simulation, operations research, or process-improvement methodologies.

Experience working with large datasets or cloud-based analytics environments.

“We are an equal opportunity employer and all qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, national origin, disability status, protected veteran status, or any other characteristic protected by law.”