8 of 8 Remote Kubeflow Jobs in the UK

algorithms , NLP , deep learning , and statistical methods. Experience with Docker, Kubernetes , and cloud platforms like AWS/Azure/GCP . Hands-on experience with MLOps tools (MLflow, SageMaker, Kubeflow, etc.) and version control systems. Strong knowledge of APIs, microservices architecture, and CI/CD pipelines. Proven experience in leading teams, managing stakeholders, and delivering end-to-end AI/ More ❯

systems. Key Responsibilities Build model lifecycle tooling (deployment, monitoring and alerting) for our predictive models (for example claims cost, conversion, retention, market models) Maintain and improve the development environment (Kubeflow) used by our Data Scientists and Actuaries Develop and maintain pricing analytics tools that enable faster impact assessments, reducing manual work Collaborate with the technical pricing, street pricing and product More ❯

knowledge of the machine learning lifecycle, from prototyping state of the art to scaling and managing for enterprise use Experience with one or more common workflow/pipelining frameworks (Kubeflow, MLFlow, Argo or equivalents) Understanding of key considerations for Ethical and Responsible AI and experience applying them Connect to your business - Technology and Transformation Distinctive thinking, deep expertise, innovation and More ❯

knowledge of the machine learning lifecycle, from prototyping state of the art to scaling and managing for enterprise use Experience with one or more common workflow/pipelining frameworks (Kubeflow, MLFlow, Argo or equivalents) Understanding of key considerations for Ethical and Responsible AI and experience applying them Connect to your business - Technology and Transformation Distinctive thinking, deep expertise, innovation and More ❯

knowledge of the machine learning lifecycle, from prototyping state of the art to scaling and managing for enterprise use Experience with one or more common workflow/pipelining frameworks (Kubeflow, MLFlow, Argo or equivalents) Understanding of key considerations for Ethical and Responsible AI and experience applying them Connect to your business - Technology and Transformation Distinctive thinking, deep expertise, innovation and More ❯

Experience: Proven background as a Machine Learning Engineer. Technical Skills: Strong in SQL and Python (Pandas, Scikit-learn, Jupyter, Matplotlib). Data transformation & manipulation : experience with Airflow, DBT and Kubeflow Cloud: Experience with GCP and Vertex AI (developing ML services). Expertise: Solid understanding of computer science fundamentals and time-series forecasting. Machine Learning: Strong grasp of ML and deep More ❯

Experience deploying machine learning models into production and managing their lifecycle. Experience implementing model governance, including versioning, monitoring, drift detection, and reporting. Familiarity with MLOps tools such as MLflow, Kubeflow, or DVC. Programming skills in Scala. Experience working with ONNX and ONNX Runtime for model optimization and deployment. Experience mentoring or supporting colleagues to help them grow their technical skills. More ❯

data and AI services 24x7. Oversee the migration and decommissioning of legacy technologies (e.g., Splunk, Jenkins, TIG), and drive adoption of modern platforms (e.g., Bindplane, Google Security Operations, VertexAI, Kubeflow, BigQuery, Harness). Risk Management: Collaborate with senior engineers, CSO, and business leaders to manage risks related to security data and AI, ensuring alignment with strategy and industry standards. Innovation More ❯