Develop and maintain data architecture: create and manage robust data architectures that support high-volume, high-throughput SaaS applications, focusing on reliability and scalability. * Strengthen data quality and model performance through well-designed ETL/ELT pipelines, streaming systems, feature store integration, and workflow orchestration. * Ensure reliable and trustworthy AI operations by implementing comprehensive observability: logs, metrics, traces, and model/data drift detection. * You have previously owned end-to-end ML/AI infrastructure — from data ingestion and feature pipelines to training, deployment, and production monitoring. * You enable data scientists to move faster by building self-service platforms, stable envi
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