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. Implement model tracking, versioning, and reproducibility practices. Deploy and manage machine learning models in cloud and production environments. Containerize applications and support scalable
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pipelines using industry-standard tools (e.g., GitHub Actions, Jenkins, Azure DevOps) for automated ML model deployment, monitoring, and retraining Design and manage hybrid cloud/on-premises environments to
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studies Professional supervision and collaboration in a dedicated team A state-of-the-art machine park equipped with edge cloud systems and 5G infrastructure Flexible working to combine study and job
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