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Actemium Deutschland

Actemium Germany: Shaping the Future with Us – Your Best Partner in Technological Advancement. Actemium is VINCI Energies' industry-focused brand. It covers the entire lifecycle of plants and systems – from planning and implementation to maintenance and repair. The goal is to improve the industrial performance of its customers. Actemium offers comprehensive expertise in automation and process control technology, electrical engineering, measurement and control technology, energy technology, and plant engineering. Through collaboration within its network, Actemium pursues both a local and global approach. With 400 business units, approximately 22,000 employees in 42 countries, and sales of around €2.8 billion, Actemium positions itself as a leading brand for industrial solutions and services. Become part of the Actemium family - Apply now: https://actemium.softgarden.io/de/vacancies Legal notice: https://www.actemium.de/impressum/ Privacy policy: https://www.actemium.de/datenschutz/

19/06/2026
Full time
Project employee AI & Data Science for Predictive Maintenance (m/f/d)
Actemium Deutschland Eigeltingen, Germany
Do you want to not only understand artificial intelligence theoretically, but also apply it in a real industrial project? Then help us shape the future of intelligent maintenance! As a Data Science & AI Project Employee for Predictive Maintenance (m/f/d), you will initially work on a one-year fixed-term project position developing data-driven solutions for assessing the condition and predicting machine failures. Together with experts from the fields of electrical engineering, service, data science, and IT, you will develop models that reduce unplanned downtime and make maintenance processes more intelligent. This is what you can expect Data analysis:   Preparation, structuring and analysis of machine, operational and service data Predictive Maintenance:   Identification of patterns, anomalies, and critical machine conditions Machine Learning:   Collaboration in the development of AI models for failure prediction and remaining lifespan...