About this role
Build and maintain data preparation and validation tooling and design ML infrastructure for model training, evaluation, and deployment; implement CI/CD pipelines, model monitoring, drift detection, and feedback loops while partnering with applied scientists and data engineering teams to productionize models.
Skills for this role
Data pipelinesML infrastructureMLOpsData preparationData validationData quality-checkingPythonSQLAWSGCPBigQueryCI/CD pipelinesModel servingBatch inferenceReal-time inferenceModel monitoringDrift detectionFeedback-loop toolingContainerizationDockerKubernetesCollaboration