1 to 25 of 89 Kubeflow Jobs in England

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 ...

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 ...

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 ...

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 ...

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 ...

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 ...

lifecycle management Lead documentation, knowledge transfer, and mentoring to upskill internal teams Technical requirements Strong Python and ML frameworks (PyTorch, TensorFlow) MLOps tooling (MLflow, Kubeflow or similar) Docker, Kubernetes, CI/CD pipelines Cloud platforms (AWS, Azure or GCP); Terraform experience preferred Financial services experience highly desirable A hands ...

lifecycle management Lead documentation, knowledge transfer, and mentoring to upskill internal teams Technical requirements Strong Python and ML frameworks (PyTorch, TensorFlow) MLOps tooling (MLflow, Kubeflow or similar) Docker, Kubernetes, CI/CD pipelines Cloud platforms (AWS, Azure or GCP); Terraform experience preferred Financial services experience highly desirable A hands ...

lifecycle management Lead documentation, knowledge transfer, and mentoring to upskill internal teams Technical requirements Strong Python and ML frameworks (PyTorch, TensorFlow) MLOps tooling (MLflow, Kubeflow or similar) Docker, Kubernetes, CI/CD pipelines Cloud platforms (AWS, Azure or GCP); Terraform experience preferred Financial services experience highly desirable A hands ...

Consulting Experience: Proven track record of delivering solutions in a client-facing consulting environment. MLOps Expertise: Hands-on experience with tools such as MLflow, Kubeflow, TensorFlow Serving, or similar. Cloud Platforms: Proficiency in multi-cloud environments (AWS, Azure, GCP). DevOps & Automation: Strong knowledge of CI/CD pipelines, containerization ...

Consulting Experience: Proven track record of delivering solutions in a client-facing consulting environment. MLOps Expertise: Hands-on experience with tools such as MLflow, Kubeflow, TensorFlow Serving, or similar. Cloud Platforms: Proficiency in multi-cloud environments (AWS, Azure, GCP). DevOps & Automation: Strong knowledge of CI/CD pipelines, containerization ...

Consulting Experience: Proven track record of delivering solutions in a client-facing consulting environment. MLOps Expertise: Hands-on experience with tools such as MLflow, Kubeflow, TensorFlow Serving, or similar. Cloud Platforms: Proficiency in multi-cloud environments (AWS, Azure, GCP). DevOps & Automation: Strong knowledge of CI/CD pipelines, containerization ...

Strong proficiency in containerisation (Docker, Kubernetes) and orchestration of multi-stage ML workflows. Hands-on experience with ML platforms and tools such as MLflow, Kubeflow, Vertex AI, SageMaker, or similar model management systems. Practical knowledge of infrastructure as code, CI/CD best practices, and cloud platforms ...

Strong proficiency in containerisation (Docker, Kubernetes) and orchestration of multi-stage ML workflows. Hands-on experience with ML platforms and tools such as MLflow, Kubeflow, Vertex AI, SageMaker, or similar model management systems. Practical knowledge of infrastructure as code, CI/CD best practices, and cloud platforms ...

Strong proficiency in containerisation (Docker, Kubernetes) and orchestration of multi-stage ML workflows. Hands-on experience with ML platforms and tools such as MLflow, Kubeflow, Vertex AI, SageMaker, or similar model management systems. Practical knowledge of infrastructure as code, CI/CD best practices, and cloud platforms ...

production environments. Knowledge of distributed training, GPU/TPU optimization, and cloud platforms (AWS, GCP, Azure). Familiarity with MLOps tools like MLflow, Kubeflow, or Vertex AI for scalable ML pipelines. Excellent leadership, communication, and cross-functional collaboration skills. Bachelor's or Master's in Computer Science, Engineering, or related ...

production environments. Knowledge of distributed training, GPU/TPU optimization, and cloud platforms (AWS, GCP, Azure). Familiarity with MLOps tools like MLflow, Kubeflow, or Vertex AI for scalable ML pipelines. Excellent leadership, communication, and cross-functional collaboration skills. Bachelor's or Master's in Computer Science, Engineering, or related ...

production environments. Knowledge of distributed training, GPU/TPU optimization, and cloud platforms (AWS, GCP, Azure). Familiarity with MLOps tools like MLflow, Kubeflow, or Vertex AI for scalable ML pipelines. Excellent leadership, communication, and cross-functional collaboration skills. Bachelor's or Master's in Computer Science, Engineering, or related ...

production environments. Knowledge of distributed training, GPU/TPU optimization, and cloud platforms (AWS, GCP, Azure). Familiarity with MLOps tools like MLflow, Kubeflow, or Vertex AI for scalable ML pipelines. Excellent leadership, communication, and cross-functional collaboration skills. Bachelor's or Master's in Computer Science, Engineering, or related ...