How to match your resume to a MLOps Engineer job description

We are looking for a MLOps Engineer to build the platform that trains, deploys and monitors models. You will automate reproducible ML pipelines, and control GPU and training spend. Required: hands-on experience with CI/CD for models, Model registry, Monitoring and drift detection, Containerisation, and working knowledge of MLflow, Kubeflow, Terraform. Preferred: Google Cloud Professional Machine Learning Engineer. Success in this role is measured by model deployment lead time, training cost per run, drift alerts resolved.

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