5 of 5 MLOps Jobs in Bath

with call/contact-centre analytics, Microsoft Teams Graph API, or telephony platforms (BroadWorks, Webex Calling). Knowledge of data governance, model ethics, and MLOps practices. Exposure to data visualization and predictive analytics for customer-experience metrics. Advanced degree in AI, ML, Data Science, or related discipline. ISTQB AI Testing ...

production-ready systems. Academic Foundation Bachelors or Masters degree in Computer Science, Machine Learning, Engineering , or a closely related discipline. Bonus Points Experience with MLOps and model serving platforms such as BentoML, MLflow, or SageMaker . Hands-on work with streaming and batch data pipelines using tools like Spark, Airflow ...

evaluation of new model architectures. · Implement production features end-to-end under guidance from senior engineers. · Participate in code reviews, testing, deployment, and MLOps workflows. · Work across internal products and contract-based venture projects. Requirements · Strong foundational programming skills in Python. · Basic understanding of AI/ML models ...

higher education. Scale platforms and solutions Take validated MVPs into production with robust architecture, integration patterns, security controls, SLAs, and operational runbooks. Establish MLOps across the university environment, including model registry, CI/CD for ML, feature stores, monitoring for drift, and retraining policies. Build reusable AI platform capabilities (e.g. … with data platforms such as Azure Data Lake, Synapse/ADF, Delta Lake, and messaging platforms (e.g., event hubs, service bus). Exposure to MLOps and observability tools (e.g., MLflow/model registry, GitHub Actions, Prometheus/Grafana, Evidently AI). Knowledge of integrating with SIS (Banner/Workday Student ...

teams Build and maintain end-to-end ML pipelines (training, validation, inference, monitoring) Ensure models meet requirements around performance, resilience, and explainability Contribute to MLOps best practices, model governance, and technical standards Support model monitoring, drift detection, and ongoing optimisation Required Experience Proven commercial experience as a Machine Learning Engineer … with cloud platforms (AWS, GCP, or Azure) Nice to Have Experience with fraud, risk, credit, AML, pricing, or customer analytics use cases Familiarity with MLOps tools (MLflow, Kubeflow, Airflow, etc.) Docker and Kubernetes experience Exposure to model governance, explainability, or regulatory frameworks Contract Details £650–£750 per day (Outside IR35 ...