9 years of hands‑on experience as a DevOps Engineer, SRE Engineer or similar role with a focus on MLOps.
Expert‑level knowledge of Kubernetes, Docker, Helm, Jenkins, ArgoCD, KubeFlow and MLFlow with a proven track record of setting up and configuring complex MLOps deployments.
Strong proficiency in scripting and automation using tools such as Bash, Python or PowerShell.
Solid understanding of CI/CD principles and best practices specifically tailored for machine learning and AI technologies.
Experience with versioning and reproducibility tools and frameworks such as Git, DVC and MLflow.
Familiarity with infrastructure‑as‑code (IaC) tools like Terraform and Ansible.
Deep understanding of Linux systems and administration.
Familiarity with cloud platforms such as AWS, Azure or GCP and the ability to deploy and manage MLOps infrastructure in a cloud environment (Azure preferred). <...
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