Establish dataset and model versioning, metadata management, quality checks, and traceability from raw sensor data to validated artifacts. * Develop AI-powered tools for internal data engineering, including semantic data search, metadata enrichment, automatic annotation, and quality assessment using foundation or multimodal models. * You have a deep understanding of the ML lifecycle, including dataset preparation, distributed training, experiment management, validation, and reproducibility. * You have worked with workflow orchestration, experiment tracking, and model or artifact management technologies such as Argo Workflows, Kubeflow, Metaflow, Airflow, MLflow, or comparable solutions.
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