AI & Automation
MLOps Engineer
Make model training, deployment, and monitoring repeatable and boring.
Build the infrastructure around ML: experiment tracking, model registries, deployment pipelines, drift monitoring, and cost controls.
Requirements
- Three or more years in MLOps, platform, or ML infrastructure roles
- Experience with containerised model serving and CI/CD for ML
- Comfortable collaborating with research-leaning ML engineers
Nice to have
- Kubeflow, MLflow, Vertex, SageMaker
- GPU cluster operations
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