INTERNSHIP DETAILS

Predictive Maintenance Co-op (Fall 2026)

CompanyBMW Group
LocationSpartanburg
Work ModeOn Site
PostedApril 3, 2026
Internship Information
Core Responsibilities
The primary focus is utilizing historical data and new analytical methods to develop strategies for avoiding failures during production runtime on critical equipment. Responsibilities include developing new monitoring concepts, planning predictive monitoring implementation, identifying opportunities for AI introduction, and proposing improvements for technical availability and failure reduction.
Internship Type
full time
Company Size
64919
Visa Sponsorship
No
Language
English
Working Hours
40 hours
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About The Company
With its four brands, BMW, MINI, Rolls-Royce and BMW Motorrad, the BMW Group is the world’s leading premium manufacturer of automobiles and motorcycles and also provides premium financial services. The BMW Group production network comprises over 30 production sites worldwide; the company has a global sales network in more than 140 countries. In 2025, the BMW Group sold 2.46 million passenger vehicles and more than 202,500 motorcycles worldwide. The profit before tax in the financial year 2025 was € 10.2 billion on revenues amounting to € 133,5 billion. As of 31 December 2025, the BMW Group had a workforce of 154,540 employees. The economic success of the BMW Group has always been based on long-term thinking and respon-sible action. Sustainability is a key element of the BMW Group’s corporate strategy and covers all products – from the supply chain through production to the end of their useful life.
About the Role

A good student experience is never hands-off. We are dedicated to fostering a dynamic learning environment where students actively engage in practical experiences throughout their time with us. From the beginning, students are entrusted with specific responsibilities, ensuring they play a significant role in their learning journey. As valued team members, students are also encouraged to share and implement their own ideas, enhancing both their personal growth and the collective success of the team.

 

Description: 

Focusing on critical production equipment, the purpose of this project is to use historical data and introduce other new analytical methods to identify key strategies to avoid failures during production run time. The new methods should be able to predict failures or have swap out strategies based on historical failure timelines and incorporate condition-based monitoring technologies.

 

The qualified intern/Co-op should expect to contribute & improve in the following functions: 

  • Develop new Concepts For monitoring techniques
  • Using a small team plan implementation of predictive monitoring.
  • Identifying opportunities Ai introduction.
  • Make proposals for the interpretation of big data.
  • Capture and plan all Automation improvement ideas and make plans transparent.
  • Put forward proposals to increase technical availability.
  • Use these proposals to track failure reduction.

 

Qualifications:

  • Preferred degree: Engineering or IT
  • Possess a minimum cumulative GPA of 3.0 (not just in major)
  • Have enrolled student status at an accredited four-year college or university in the United States.
  • Completed at least 30 credit hours at time of application.
  • Ability to work full-time on-site (40 hours / week).
  • Transfer students must have a GPA from current university.
  • MUST ATTACH A COPY OF UNOFFICIAL TRANSCRIPT
  • Complete and pass a substance abuse test before the work term.
  • THE WORK TERM DATES ARE August 10th – December 11th, 2026.
  • Must be an enrolled student during all three rotations.

 

BMW Manufacturing Company is an equal opportunity employer. It is the policy of BMW MC to provide equal employment opportunity (EEO) to all qualified persons regardless of age, race, color, religion, sex, sexual orientation, gender identity, national origin, disability or veteran status. 

Key Skills
Predictive MaintenanceData AnalysisAnalytical MethodsFailure PredictionCondition-Based MonitoringMonitoring TechniquesImplementation PlanningArtificial IntelligenceBig Data InterpretationAutomation ImprovementTechnical Availability IncreaseFailure Reduction Tracking
Categories
EngineeringManufacturingData & AnalyticsScience & Research