scale ML platforms and products (ideally using AWS SageMaker). Proven experience delivering ML solutions from data ingestion and feature engineering through to production deployment, monitoring, and continuous improvement. Experience building reliable, low‐latency inference services and operating ML workloads at scale. Proven experience solving scaling, reliability, and operational … challenges for enterprise ML systems. Technical Leadership & Architecture Defining end‐to‐end ML architectures spanning data pipelines, feature engineering, model training, deployment, inference, monitoring, and telemetry. Establishing engineering standards and operational excellence. Implementing feature stores, Lakehouse architectures, and enterprise data quality frameworks. Coaching engineers, reviewing designs, and driving technical ...
