4 of 4 Permanent MLOps Jobs in the East Midlands

Event Hubs, or Kinesis for real-time data processing Knowledge of data architectures supporting AI/ML workloads, including vector databases, feature stores and MLOps pipelines Experience processing and managing unstructured data types (text, images, logs, sensor data) Understanding of Lambda and Kappa architectural patterns and when to apply each ...

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 ...

Advanced Python development skills. Experience building scalable AI services and APIs. Strong backend development and integration experience. Knowledge of software engineering best practices and MLOps workflows. Experience with Microsoft Azure (preferred), AWS, or Google Cloud Platform. Experience designing microservices-based and distributed architectures. Expertise in experiment design and scientific evaluation … Electrical & Electronic Engineering Related STEM discipline Computer Vision and image understanding systems. AI agent frameworks and autonomous workflows. Knowledge graphs and semantic retrieval systems. MLOps and model deployment pipelines. Team leadership or technical management experience. Additional Information We bring together entrepreneurial, tech-driven people to deliver innovative solutions for leading ...

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 ...