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
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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