Einleitung

Aufgaben

• Support MLOps Engineers in building and maintaining end-to-end ML workflows, from data preparation and model training to testing and deployment
• Assist in setting up and improving reproducible ML training pipelines and experiment workflows
• Help prepare, validate, and manage datasets used for ML model training, evaluation, and testing
• Support the execution, comparison, and documentation of ML model experiments, including relevant metrics and configurations
• Assist in monitoring ML pipelines, model performance, system availability, and resource usage through dashboards
• Perform maintenance and troubleshooting tasks for ML-related IT systems such as JupyterHub, CI pipelines, and compute environments

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Qualifikationen

• Strong interest in understanding end-to-end ML processes in practice and contributing to different parts of the ML pipeline
• Motivated to build reliable, robust, and well-structured IT and MLOps processes, with a fundamental interest in understanding how systems work
• Analytical problem-solving skills, attention to detail, and the ability to identify areas for improvement
• Good programming skills, preferably in Python, and ideally experience from practical programming projects
• Experience with Linux server administration; knowledge of Docker or virtualization is a plus
• Nice to have: basic knowledge of Machine Learning, Grafana or dashboarding tools, GitLab CI/CD pipelines, or Kubernetes
• Open and proactive communication style, including willingness to ask questions, seek support, and collaborate with the team

Kontakt und weitere Informationen

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