Machine Learning Engineer
hertfordshire, east anglia, united kingdom
Hybrid / WFH Options
Hybrid / WFH Options
Rightmove
/recovery processes. Using MLOps tools (e.g., Vertex Pipelines, Kubeflow, Weights & Biases) for experiment tracking, model registry, and automated deployment. Leveraging Docker/Kubernetes and workflow orchestration tools (Airflow, Prefect, Dagster). Collaborating with product, design, and engineering teams to deliver ML features that directly impact customer experience. Translating model performance into business metrics (e.g., accuracy vs cost/latency … organizations or teams operating at significant scale (e.g., web-scale, distributed systems, cloud-native environments). Brings expertise in MLOps: CI/CD pipelines, Docker, Kubernetes, workflow orchestration (Airflow, Prefect), and automation. Has experience across and understands the full ML lifecycle. Can design for long-term scalability, reliability, and resilience. Has strong programming skills with Python – essential. Has hands-on More ❯
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