1 of 1 Remote Observability Jobs in Buckinghamshire

scientists to take models from development to production-grade systems, ensuring scalability, reproducibility, and robustness. Automating feature engineering and data pipeline processes, ensuring reproducibility and auditability. Implementing monitoring and observability to detect drift, bias, and performance degradation, and setting up rollback/recovery processes. Using MLOps tools (e.g., Vertex Pipelines, Kubeflow, Weights & Biases) for experiment tracking, model registry, and automated … distributed systems). 3+ years of experience as an ML Engineer, MLOps Engineer, Data Engineer, or similar, in a larger-scale, production-focused environment. Hands-on with model monitoring, observability, and retraining pipelines. Exposure to feature stores, registries, and experimentation frameworks. Familiarity with business-driven metrics and experience balancing ML performance with commercial goals. Experience with generative AI and LLM More ❯