Deep Learning and Machine Learning Engineer in Production

vor 2 Wochen


Aachen, Nordrhein-Westfalen, Deutschland Fraunhofer-Gesellschaft Vollzeit

In the realm of manufacturing, Deep Learning (DL) and Machine Learning (ML) have been successfully applied in a wide variety of use cases. Examples include the production of rockets, stem cells to fight blood cancer, optics, or lightweight components. In these applications, tabular and image data are recorded during production. In the context of this position, DL and ML pipelines are to be created for the applications of the production, which are then directly taken into operation in our industry projects.

Key Responsibilities

  • Collaboration with experts to create and prepare image and tabular data
  • Implementation of DL and ML models depending on the use case
  • Comparison of DL- and ML-based methods with methods of classical data analysis
  • Validation and documentation of results

Requirements

  • Studying mechanical engineering, computer science, industrial engineering, or a comparable subject
  • Experience in the field of machine learning is an advantage
  • A high degree of initiative and team spirit
  • Very good language skills in German and English

What We Offer

  • An excellent equipment of machines and devices
  • Collaboration in industry or industry-oriented research projects and in a dedicated team
  • Space for creative work

We value and promote the diversity of our employees' skills and therefore welcome all applications - regardless of age, gender, nationality, ethnic and social origin, religion, ideology, disability, sexual orientation, and identity.

Fraunhofer plays a central role in the innovation process with its focus on developing key technologies that are vital for the future and enabling the commercial utilization of this work by business and industry. As a pioneer and catalyst for groundbreaking developments and scientific excellence, Fraunhofer helps shape society now and in the future.

Interested? Apply online now.

Questions according to this position will be answered by: Dr. Maik Frye, Research assistant production quality



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