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Senior MLOps Engineer
The ML lifecycle, production-grade. Hired from LatAm, working your exact US hours, presented in a curated shortlist in under five days.
A senior MLOps Engineer owns everything between a trained model and a reliable product feature: pipelines, versioning, deployment automation, and drift detection.
What they own
- Training pipeline automation
- Model registry, versioning, and governance
- Deployment and rollback automation for models
- Drift detection and retraining triggers
Typical stack
MLflowKubeflowSageMakerVertex AIDockerAirflow
Why senior matters here
Models rot silently. A senior MLOps engineer has watched drift destroy a product metric and builds the monitoring that catches it next time.
Need a senior MLOps Engineer on your team?
One fixed all-inclusive rate. No recruiting fees, no replacement fees. Shortlist in under five days.