Machine Learning Engineering

Engineer training pipelines, features, model artifacts, batch or online serving, performance, testing, deployment interfaces and resilience. Use for ML Engineer implementation and productionization work. Route general batch, CDC or streaming ingestion to data-engineering, and registry, drift or model rollout operations to mlops.

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npx skillmds@latest add kina2711/machine-learning-engineering