Future ML engineers will not only build models but also deploy, monitor, and maintain them reliably. Understanding continuous integration/continuous deployment (CI/CD) pipelines, containerization (Docker), and orchestration (Kubernetes) will be critical. Data analysts should start gaining experience with MLOps frameworks to manage the lifecycle of machine learning models efficiently.
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