7 of 7 Remote Kubeflow Jobs in London

versioning. 4. MLOps & Automation Implement MLOps practices including CI/CD for ML, model versioning, and experiment tracking. Use tools such as MLflow, Kubeflow, SageMaker, Vertex AI, or Azure ML. Automate model training, testing, deployment, and monitoring workflows. 5. Cloud & Infrastructure Build ML solutions on cloud platforms such ...

versioning. 4. MLOps & Automation Implement MLOps practices including CI/CD for ML, model versioning, and experiment tracking. Use tools such as MLflow, Kubeflow, SageMaker, Vertex AI, or Azure ML. Automate model training, testing, deployment, and monitoring workflows. 5. Cloud & Infrastructure Build ML solutions on cloud platforms such ...

Azure), including large-scale ML infrastructure management. Knowledge of GPU computing for model training and serving. Experience managing containerised workloads (Docker, Kubernetes, Kubeflow, etc.) and integrating with CI/CD tools (Jenkins, GitHub Actions, GitLab CI). Familiarity with distributed computing frameworks (Spark, Ray, TensorFlow Distributed, PyTorch Distributed). Strong ...

Azure), including large-scale ML infrastructure management. Knowledge of GPU computing for model training and serving. Experience managing containerised workloads (Docker, Kubernetes, Kubeflow, etc.) and integrating with CI/CD tools (Jenkins, GitHub Actions, GitLab CI). Familiarity with distributed computing frameworks (Spark, Ray, TensorFlow Distributed, PyTorch Distributed). Strong ...

with large datasets and data pipelines Desirable Experience Experience with Generative AI or large language models Exposure to tools such as Hugging Face, MLflow, Kubeflow, or similar Knowledge of NLP, computer vision, or recommendation systems Experience working in agile or product-led environments Whats on Offer Competitive salary and benefits ...

models, and vector databases. Experience with cloud platforms (AWS, GCP, Azure) and AI/ML services. Knowledge of MLOps tools and practices (e.g., MLflow, Kubeflow, Vertex AI, Azure ML). Strong understanding of data engineering, data pipelines, and ETL workflows. Excellent problem-solving, communication, and stakeholder engagement skills. Bachelor ...

models, and vector databases. Experience with cloud platforms (AWS, GCP, Azure) and AI/ML services. Knowledge of MLOps tools and practices (e.g., MLflow, Kubeflow, Vertex AI, Azure ML). Strong understanding of data engineering, data pipelines, and ETL workflows. Excellent problem-solving, communication, and stakeholder engagement skills. Bachelor ...