3 of 3 Permanent Canary Deployment Jobs in Central London

. Build, Integrate & Automate: Guide engineering on LLMOps/MLOps (model lifecycle, feature stores, CI/CD for ML, telemetry, A/B & canary releases) and integrate with DevOps toolchains; automate infra as code and pipelines for AI services. Orchestrate data and model services via microservices , event-driven ...

with attention to reliability patterns (dead-letter queues, safe reprocessing, backpressure). AI/ML Operations Support • Partner with the ML engineer on production deployment of AI/ML models and agentic workflows: containerisation, versioning, controlled rollouts, and regression testing. • Implement operational controls for LLM usage in production: rate … language (Python strongly preferred, given the ML stack; Go, C#, or TypeScript also valuable). • Experience with containers (Docker, Kubernetes or equivalent) and modern deployment patterns (blue-green, canary, feature flags). • Production experience with monitoring, logging, and alerting systems, and a track record of responding ...

infrastructure and operational lifecycle of the machine learning systems that power our clinical monitoring platform. You will build and maintain the production ML pipelines, deployment infrastructure, and monitoring systems that enable Circadia's predictive models to identify early signs of clinical deterioration. Reporting to the Principal ML Engineer … always improving. Key Responsibilities ML Pipeline Orchestration & Automation Own and extend Circadia’s ML pipeline orchestration using Apache Airflow, including training, evaluation, and deployment workflows. Build and maintain automated pipelines for model retraining, validation, and promotion across development, staging, and production environments. Implement pipeline monitoring, alerting, and failure recovery ...