8 of 8 Kubeflow Jobs in the South East

GCP, or Azure). Solid understanding of CI/CD pipelines and automated testing frameworks. Experience with ML frameworks such as PyTorch, TensorFlow, or Scikit-learn. Familiarity with MLflow, Kubeflow, DVC, or similar MLOps tools . Understanding of cloud security principles , IAM, and networking best practices. Proficiency in Python and Bash scripting for automation and tooling development. Version control with More ❯

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 deployment. Leveraging Docker/Kubernetes and workflow orchestration tools (Airflow, Prefect, Dagster). Collaborating with product, design, and engineering teams to More ❯

in applied data science, machine learning, or analytics leadership. • Strong understanding of model lifecycle management, experimentation frameworks, and data science governance. • Familiarity with MLOps concepts and tooling (e.g., MLflow, Kubeflow, Vertex AI, SageMaker, Azure ML). • Hands-on experience with data science tools and languages such as Python, R, SQL, and relevant frameworks (e.g., scikit-learn, TensorFlow, PyTorch). • Proven More ❯

Solid CI/CD engineering with GitHub Actions and/or Argo CD. Preferred/Bonus - Research experience in edge AI or constrained/offline deployments. - MLOps experience (Sagemaker, Kubeflow, ZenML). - Experience building RESTful services around AI pipelines. - ISO 27001, NIST SSDF, OWASP SAMM, or GDPR compliance literacy. - Experience with AWS Karpenter, Prometheus, or similar observability stacks. Soft Skills 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 ❯

IaC (Terraform/CloudFormation) Proficiency with containerisation (Docker) and Kubernetes-based environments A passion for experimentation , research, and bridging theory with practice Bonus if you have: MLOps experience (SageMaker, Kubeflow, ZenML) Research or deployments in edge AI or constrained environments Experience building REST APIs around AI systems Familiarity with ISO 27001 , GDPR , or NIST SSDF The Offer Permanent role with More ❯

CD . What Will Make You Stand Out Prior research or applied experience in edge AI or constrained/offline deployment scenarios. Direct experience with MLOps platforms like Sagemaker, Kubeflow, or ZenML. Proficiency in building RESTful services to expose AI pipelines. Literacy in security and governance standards (e.g., ISO 27001, NIST SSDF). Experience with advanced cloud orchestration tools like … Data Scientist, Artificial Intelligence, AWS, Terraform, Kubernetes, EKS, Docker, Containerisation, Python, Go, Bash, CI/CD, GitHub Actions, Argo CD, Edge AI, Offline AI, MOD Clearance, Security Clearance, Sagemaker, Kubeflow, ZenML, AI Architect, Solution Architect. More ❯

Machine Learning Engineer (Python/MLE ) 6 Month Contract £650 - £750 Remote Umbrella Urgent Start We are looking for a number of MLE/Machine Learning Engineers for a critical 6 month contract with a household name. This role is More ❯