ML Ops Engineer

ML Ops engineers build the infrastructure that lets ML models actually live in production — training pipelines, feature stores, model registries, monitoring, retraining workflows. Think DevOps, but for models, with extra fun around data drift.

Tuning a training pipeline, debugging a feature freshness issue, deploying a new model version, and setting up drift alerts.