4 of 4 Kubeflow Jobs in the Thames Valley

NumPy, Scikit-learn, TensorFlow, PyTorch). Hands-on experience implementing end-to-end ML pipelines (data ingestion, training, validation, serving). Familiarity with ML workflow orchestration tools (Airflow, Prefect, Kubeflow) and feature/data platforms (Databricks, Tecton, etc.). Strong experience with cloud platforms (AWS, GCP, or Azure), Docker, and Kubernetes. Solid coding practices, including Git, automated testing, and CI More ❯

. Prompt Engineering, Langchain, Langsmith/Langfuse, Gen AI/Agentic AI, Cloud platforms (Azure AI Foundry, AWS Sagemaker/Bedrock, GCP Vertex AI), MLOps/LLMOps tools (MLflow, Kubeflow, Docker, Kubernetes). Preferred Delivered AI projects within Agile frameworks Experience on Model Feedback Analysis, topic modelling, sentiment analysis Knowledge of AgentOps and OpenTelemetry Understanding of Network Security Concepts, Network More ❯

monitoring, logging, and performance testing for GPU/ML workloads. Excellent collaboration skills — able to work with research, engineering, and product teams. Desirables: Experience in MLOps/LLMOps (MLflow, Kubeflow, Weights & Biases, experiment tracking). Exposure to video processing, compression, or neural rendering pipelines. Knowledge of FPGA/embedded deployment Contributions to open-source GPU/ML/DevOps projects. More ❯

and Expertise You will have relevant academic (research Masters level) and/or industry experience. Excellent knowledge and experience of managing an on-premise Kubenetes cluster. Excellent knowledge of Kubeflow and similar systems, e.g. MLflow Good programming ability in Python with familiarity with Linux systems including scripting and system configuration. Experience using AWS, e.g, Cognito, S3, EC2, Lamdas, etc. Experience More ❯