Master's thesis: Adaptation of MLOps for the integration of AI/ML in maintenance

Your tasks :

• Literature and market research on current trends and technologies in the field of MLOps and their application in maintenance
• Analysis of specific maintenance requirements for AI/ML models and their operation
• Development of an adapted MLOps approach that facilitates the integration of AI/ML in maintenance
• Derivation of recommendations for action and creation of practice-oriented documentation

Your profile:

• You are studying industrial engineering, mechanical engineering, computer science or similar
• You have very good written and spoken English skills
• You are characterized by an independent and committed as well as careful and goal-oriented way of working
• You are confident in using the common MS Office programs

The Service Management department optimizes processes in the operation, maintenance and repair of technical systems. We use modern technologies and innovative concepts to create sustainable added value. MLOps play a decisive role in efficiently implementing data-driven approaches in the context of AI and ML.

Thesis objective : The aim of your thesis is to adapt MLOps approaches specifically to the use case of maintenance. You will develop an approach that enables the effective use of AI/ML in maintenance processes and is supported by MLOps. Based on your results, you will derive recommendations for the implementation of customized MLOps pipelines.

Our offer:

• Insights into the industrial and research business in collaboration with well-known companies and research partners
• Interesting, challenging and varied tasks in a qualified and dynamic team
• The opportunity for flexible time management and independent work
• A modern, collegial and digital working environment
• Room for creativity and your personal development