About the role#
This is a part-time, paid internship at KION Group. You will work on-site in Grand Rapids, Michigan. The position follows a rolling term schedule.
What you'll do#
- Gain practical experience implementing GenAI and Agentic AI use cases.
- Contribute to ongoing projects while learning from real-world challenges.
- Assist the team with research, data analysis, and development tasks.
- Participate in team meetings, trainings, and presentations.
What you'll need#
- Current enrollment in a bachelor's degree program for Computer Science, Computer Engineering, Electrical Engineering, Mechanical Engineering, or Business Administration.
- Preference for students entering their Junior or Senior year.
- Strong communication and interpersonal skills.
- Ability to work independently and as part of a team.
Location & details#
- Location: Grand Rapids, Michigan.
- Schedule: Part-time, on-site.
- Compensation: Estimated at $21-$25 per hour.
About KION Group
KION Group operates in the machinery manufacturing industry, focusing on supply chain solutions and industrial trucks. Founded in 2006, the company maintains a global presence with headquarters in Frankfurt, Germany. It employs over 42,000 people across its various brands, including Dematic, Linde Material Handling, and STILL. The firm provides automation technology and equipment for both premium and economy market segments.
How to get in at KION Group
Securing an internship at KION Group requires speed, as early applicants often gain visibility before the candidate pool becomes unmanageable. Intern Insider sends an instant alert the moment a role matching your target is published, helping you apply among the first. This timing ensures your materials are reviewed while recruiters are still actively building their shortlist. You can also improve your chances by reaching out to the people managing these positions directly. Intern Insider surfaces the recruiters behind KION Group roles, allowing you to ask relevant questions or request a referral. This direct approach often leads to better response rates than submitting an application into a general queue.
