10 of 10 Kubeflow Jobs in the UK excluding London

GPT, BERT, T5 family). • Familiarity with on-device or edge-AI deployments (e.g., TensorFlow Lite, ONNX, mobile/embedded inference). • Knowledge of MLOps tooling (MLflow, Weights & Biases, Kubeflow, or similar) for experiment tracking and model governance. • Open-source contributions or published papers in top-tier AI/ML conferences (NeurIPS, ICML, CVPR, ACL, etc.). ⸻ Soft Skills & Cultural More ❯

hiring. 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 the Data Scientists Develop and maintain pricing analytics tools that enable faster impact assessments, reducing manual work Collaborate with the technical pricing, street pricing and product teams to More ❯

shell scripting and performance tuning. Nice to have: Certifications in Kubernetes, Ceph, or cloud technologies (AWS/GCP/Azure). Familiar with with ML infrastructure: Ray (KubeRay), MLFlow, KubeFlow, Nexus (Pypi) or model serving platforms. Familiar with Git, GitOps workflows to aid the Infrastructure-as-code Experience with service mesh technologies like Istio. Willing to dabble in Python Benefits More ❯

Knowledge of cutting-edge techniques for Natural Language Processing and Computer Vision Strong grasp of basic probability concepts and machine learning lifecycle Experience with workflow and pipelining frameworks (e.g., Kubeflow, MLFlow, Argo) Understanding and application of Ethical AI considerations Ready to take your career to the next level? Apply today and be part of something extraordinary! Please either apply by More ❯

MAUs. Your First 12 Months Ship V1 of the food-analysis API (image + text → nutrient vector → protocol tag) with Stand-up an ML Ops stack (Vertex AI/Kubeflow, Terraform-managed infra) that supports rapid retraining and audit logs. Scale the team—hire or upskill research engineers, data scientists and backend developers; formalise career ladders and a high-trust More ❯

with version controls systems (e.g. Git) Desirables: Experience with cloud-based ML infrastructure, particularly GCP (Vertex AI, BigQuery), or equivalent (e.g. AWS, Azure) Exposure to orchestration tools such as Kubeflow pipelines or Airflow Familiarity with DBT or similar tools for modelling data in data warehouses Desire to build interpretable and explainable ML models (using techniques such as SHAP) Desire to More ❯

with version controls systems (e.g. Git) Desirables: Experience with cloud-based ML infrastructure, particularly GCP (Vertex AI, BigQuery), or equivalent (e.g. AWS, Azure) Exposure to orchestration tools such as Kubeflow pipelines or Airflow Familiarity with DBT or similar tools for modelling data in data warehouses Desire to build interpretable and explainable ML models (using techniques such as SHAP) Desire to More ❯

with version controls systems (e.g. Git) Desirables: Experience with cloud-based ML infrastructure, particularly GCP (Vertex AI, BigQuery), or equivalent (e.g. AWS, Azure) Exposure to orchestration tools such as Kubeflow pipelines or Airflow Familiarity with DBT or similar tools for modelling data in data warehouses Desire to build interpretable and explainable ML models (using techniques such as SHAP) Desire to More ❯

guiding organisations through early-stage discovery. Desirable: Certifications in Data Architecture, Governance, or Cloud. Experience working with or implementing DDOM frameworks. Understanding of ML Ops tools (e.g., MLflow, SageMaker, Kubeflow) and data privacy regulations (GDPR, CCPA). More ❯

across disciplines. ● Experience integrating or leveraging Large Language Models (LLMs) via APIs or platform services (e.g., OpenAI, Anthropic, Cohere). ● Familiarity with MLOps tools and practices (e.g., MLflow, SageMaker, Kubeflow). ● Experience in startup or fast-paced environments with rapidly evolving requirements Personal qualities ● Ambitious ● Driven ● Ability to work as part of a collaborative team but also work independently ● Strong More ❯