2 of 2 MLOps Jobs in Nottingham

ingestion and feature engineering to production deployment and monitoring. The role focuses on building scalable, low-latency ML systems and establishing robust governance and MLOps practices. The successful candidate will lead design and implementation of end-to-end ML architectures, coach engineers, and ensure alignment with enterprise standards, while delivering ...

successful, production‐scale machine learning solutions (ideally on AWS SageMaker). You will provide technical leadership across ML lifecycle, including defining architecture, engineering standards, MLOps practices, and governance frameworks for a large‐scale matching platform. This is a hands‐on lead role requiring recent expertise in building, deploying, monitoring … Establishing engineering standards and operational excellence. Implementing feature stores, Lakehouse architectures, and enterprise data quality frameworks. Coaching engineers, reviewing designs, and driving technical direction. MLOps, Deployment & Operations Deep hands‐on experience with SageMaker Pipelines, Training, Processing, Model Registry, Endpoints, Monitoring, and deployment workflows. CI/CD, infrastructure as code, model ...