Working Student Position - Deployment Administration

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Kubernetes Cluster and Deployment Administration for Applied Machine Intelligence Lecture

Applied Machine Intelligence

This course teaches concepts of information extraction using machine learning in various applications taking into account constraints in realistic use-cases. Typical topics are:

  • Lifecycle of a Machine Learning task
  • Data Preprocessing
  • Regression (Algorithms and Metrics)
  • Classification (Algorithms and Metrics)
  • Deep Learning
  • Active Learning
  • Model Selection
  • Validation Techniques
  • Model Interpretation

Task Description

In this working student position you work on the following topics:

  • Setup and maintain a Kubernetes Cluster on an LRZ Server machine
  • Provide access for participants of the Applied Machine Intelligence lecture
  • Support students to deploy their projects on the cluster
  • Integrate Data Science Storage by LRZ
  • Provide access to virtual Nvidia GPUs for each project group on the server machine


  • Intermediate knowledge of Kubernetes and Docker
  • Intermediate knowledge of version control systems (Git)
  • Interest in system administration and IT technology
  • High motivation and independent way of working, proactive and self-organized commitment
  • Team player skills

Our offerings

  • Integration in a team of data researchers at the Chair of Data Processing
  • Work can be done completely from a remote position if required
  • The payment is in the usual range for student assistants
  • Start from approx. beginning of April until approx. middle of July
  • The duration of work is approximately 6 hours per week, but this can be flexibly adjusted.
  • Access to student rooms and equipment
  • Unlimited supply of coffee (personal use only)