51 to 75 of 277 Containerisation Jobs in the Midlands

well as the management of cloud-based platforms, such as Azure, AWS and Google Cloud. The Senior Platform Engineer work with infrastructure as code, containerisation, and modern CI/CD practices. They will also work with other members of the team to develop and implement DevOps practices, and mentor more ...

well as the management of cloud-based platforms, such as Azure, AWS and Google Cloud. The Senior Platform Engineer work with infrastructure as code, containerisation, and modern CI/CD practices. They will also work with other members of the team to develop and implement DevOps practices, and mentor more ...

well as the management of cloud-based platforms, such as Azure, AWS and Google Cloud. The Senior Platform Engineer work with infrastructure as code, containerisation, and modern CI/CD practices. They will also work with other members of the team to develop and implement DevOps practices, and mentor more ...

well as the management of cloud-based platforms, such as Azure, AWS and Google Cloud. The Senior Platform Engineer work with infrastructure as code, containerisation, and modern CI/CD practices. They will also work with other members of the team to develop and implement DevOps practices, and mentor more ...

well as the management of cloud-based platforms, such as Azure, AWS and Google Cloud. The Senior Platform Engineer work with infrastructure as code, containerisation, and modern CI/CD practices. They will also work with other members of the team to develop and implement DevOps practices, and mentor more ...

well as the management of cloud-based platforms, such as Azure, AWS and Google Cloud. The Senior Platform Engineer work with infrastructure as code, containerisation, and modern CI/CD practices. They will also work with other members of the team to develop and implement DevOps practices, and mentor more ...

well as the management of cloud-based platforms, such as Azure, AWS and Google Cloud. The Senior Platform Engineer work with infrastructure as code, containerisation, and modern CI/CD practices. They will also work with other members of the team to develop and implement DevOps practices, and mentor more ...

well as the management of cloud-based platforms, such as Azure, AWS and Google Cloud. The Senior Platform Engineer work with infrastructure as code, containerisation, and modern CI/CD practices. They will also work with other members of the team to develop and implement DevOps practices, and mentor more ...

Mastery: Hands-on experience with Management Zones, Request Attributes, Tagging Rules, and Alert Profiles. Architecture Knowledge: Deep understanding of multi-tier architectures and microservices. Containerization: Experience monitoring Kubernetes, OpenShift, or Docker environments. Cloud Expertise: Familiarity with AWS, Azure, or GCP. Protocols: Strong understanding of HTTP/S, TCP/ ...

Tencent Cloud, covering compute, storage, networking, and managed services Develop and maintain GitLab CI/CD pipelines to automate builds, testing, security checks, containerisation, and deployment Create robust, reusable Terraform modules to provision and manage Tencent Cloud infrastructure Manage and optimise Kubernetes clusters, including autoscaling, resource allocation, security policies ...

Tencent Cloud, covering compute, storage, networking, and managed services Develop and maintain GitLab CI/CD pipelines to automate builds, testing, security checks, containerisation, and deployment Create robust, reusable Terraform modules to provision and manage Tencent Cloud infrastructure Manage and optimise Kubernetes clusters, including autoscaling, resource allocation, security policies ...

DevOps & CI/CD - Strong grasp of DevOps principles. Experience with Azure DevOps, GitHub Actions, Jenkins. AZ-400 certification desirable Containerisation - Experience with AKS/EKS, Proficiency in AWS CloudFormation or ARM templates Scripting & Automation - Proficient in PowerShell, Bash, or Python Infrastructure as Code (IaC) - Hands-on experience with Terraform ...

testing Ability to work collaboratively in a team environment Desirables Azure cloud experience (App Services, Functions, Storage, Service Bus, etc.) Exposure to microservices or containerisation (Docker/Kubernetes) Experience with front-end frameworks such as React or Vue The Company This company is a recognised leader in the financial services ...

Automate model training, testing, deployment, and monitoring workflows. 5. Cloud & Infrastructure Build ML solutions on cloud platforms such as AWS, Azure, or GCP. Use containerization and orchestration tools (Docker, Kubernetes). Optimize compute costs and performance for training and inference workloads. 6. Collaboration & Stakeholder Engagement Work closely with Data Scientists ...

Automate model training, testing, deployment, and monitoring workflows. 5. Cloud & Infrastructure Build ML solutions on cloud platforms such as AWS, Azure, or GCP. Use containerization and orchestration tools (Docker, Kubernetes). Optimize compute costs and performance for training and inference workloads. 6. Collaboration & Stakeholder Engagement Work closely with Data Scientists ...

Automate model training, testing, deployment, and monitoring workflows. 5. Cloud & Infrastructure Build ML solutions on cloud platforms such as AWS, Azure, or GCP. Use containerization and orchestration tools (Docker, Kubernetes). Optimize compute costs and performance for training and inference workloads. 6. Collaboration & Stakeholder Engagement Work closely with Data Scientists ...

Automate model training, testing, deployment, and monitoring workflows. 5. Cloud & Infrastructure Build ML solutions on cloud platforms such as AWS, Azure, or GCP. Use containerization and orchestration tools (Docker, Kubernetes). Optimize compute costs and performance for training and inference workloads. 6. Collaboration & Stakeholder Engagement Work closely with Data Scientists ...

Automate model training, testing, deployment, and monitoring workflows. 5. Cloud & Infrastructure Build ML solutions on cloud platforms such as AWS, Azure, or GCP. Use containerization and orchestration tools (Docker, Kubernetes). Optimize compute costs and performance for training and inference workloads. 6. Collaboration & Stakeholder Engagement Work closely with Data Scientists ...

Automate model training, testing, deployment, and monitoring workflows. 5. Cloud & Infrastructure Build ML solutions on cloud platforms such as AWS, Azure, or GCP. Use containerization and orchestration tools (Docker, Kubernetes). Optimize compute costs and performance for training and inference workloads. 6. Collaboration & Stakeholder Engagement Work closely with Data Scientists ...

Automate model training, testing, deployment, and monitoring workflows. 5. Cloud & Infrastructure Build ML solutions on cloud platforms such as AWS, Azure, or GCP. Use containerization and orchestration tools (Docker, Kubernetes). Optimize compute costs and performance for training and inference workloads. 6. Collaboration & Stakeholder Engagement Work closely with Data Scientists ...

Automate model training, testing, deployment, and monitoring workflows. 5. Cloud & Infrastructure Build ML solutions on cloud platforms such as AWS, Azure, or GCP. Use containerization and orchestration tools (Docker, Kubernetes). Optimize compute costs and performance for training and inference workloads. 6. Collaboration & Stakeholder Engagement Work closely with Data Scientists ...

Automate model training, testing, deployment, and monitoring workflows. 5. Cloud & Infrastructure Build ML solutions on cloud platforms such as AWS, Azure, or GCP. Use containerization and orchestration tools (Docker, Kubernetes). Optimize compute costs and performance for training and inference workloads. 6. Collaboration & Stakeholder Engagement Work closely with Data Scientists ...

Automate model training, testing, deployment, and monitoring workflows. 5. Cloud & Infrastructure Build ML solutions on cloud platforms such as AWS, Azure, or GCP. Use containerization and orchestration tools (Docker, Kubernetes). Optimize compute costs and performance for training and inference workloads. 6. Collaboration & Stakeholder Engagement Work closely with Data Scientists ...

Automate model training, testing, deployment, and monitoring workflows. 5. Cloud & Infrastructure Build ML solutions on cloud platforms such as AWS, Azure, or GCP. Use containerization and orchestration tools (Docker, Kubernetes). Optimize compute costs and performance for training and inference workloads. 6. Collaboration & Stakeholder Engagement Work closely with Data Scientists ...

Automate model training, testing, deployment, and monitoring workflows. 5. Cloud & Infrastructure Build ML solutions on cloud platforms such as AWS, Azure, or GCP. Use containerization and orchestration tools (Docker, Kubernetes). Optimize compute costs and performance for training and inference workloads. 6. Collaboration & Stakeholder Engagement Work closely with Data Scientists ...