351 to 375 of 1,348 Containerisation Jobs in the UK excluding London

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 ...

Microsoft SQL Server and data structure design skills. Modern Tooling: Experience with CI/CD (TeamCity/Octopus), Version Control (Bitbucket/Git), and Containerisation (Docker/Kubernetes). Leadership & Grit: You lead by example. Energy, ambition, and "grit" matter more to us than years of formal management experience. Education ...

specifications and prototypes. About you: Extensive experience in software engineering with a strong focus on Python. Proven expertise in cloud platforms, specifically AWS, and containerization tools. Strong practical knowledge of Terraform and DevOps methodologies. Experience working within the Healthcare sector or Government (DDaT) environments is highly desirable. Understanding of Agile ...

Working with 3D geometry or FEA/CFD simulation tools Cloud infrastructure (AWS, Azure) and tools like Terraform CI/CD pipelines and containerisation Machine learning model development or agentic AI workflows Infrastructure automation and scalable deployment systems Mechanical design principles and turbomachinery fundamentals Ideal for someone with ...

experience architecting and delivering enterprise solutions with ReactJS React Native NET Core and Azure Deep understanding of cloud native architectures microservices API management and containerization Docker Kubernetes Handson expertise with Azure services App Service Functions AKS API Management Cosmos DB Blob Storage Logic Apps Azure DevOps Experience integrating with authentication ...

analytical skills. Excellent communication and teamwork skills. Nice-to-Have: Experience with CI/CD pipelines using tools like GitHub Actions. Experience with containerization (eg, Docker). Familiarity with serverless architectures. Experience with SonarCloud or Snyk for code quality and security. Familiarity with TurboRepo for managing monorepos. Knowledge of Storybook ...

Stack PHP Developer, with excellent Laravel, PHP, JavaScript (ideally Vue.JS) & Cloud (AWS or Azure) experience is required by a leading company based in Preston. Containerisation, TDD or .NET skills would be a bonus. Due to investment and a pipeline of brand-new green field work, they need a couple ...

tolerance, disaster recovery, and enterprise-grade resilience. Migration Planning & Execution Assess existing infrastructure, applications, and workloads for migration readiness. Develop comprehensive migration strategies covering containerization, workload transfer, and data migration. Implement migration processes with minimal downtime and operational disruption. Identify risks and implement mitigation strategies for smooth migration. VMware & Pure ...

applications. Knowledge of vector databases (FAISS, Pinecone, Weaviate) and graph technologies (Neo4j). Familiarity with observability tools and AI evaluation frameworks. Strong grasp of containerization and cloud deployment (Docker, AWS, Azure). Tools & Platforms GitHub Copilot, ChatGPT/GPT-4, Claude for AI-assisted development. LangChain, LlamaIndex for RAG implementations. ...

pipelines for near-real-time detection (packet/flow analytics). Background in resilience engineering, chaos testing, disaster recovery, and capacity planning at hyperscale. Containerization/orchestration (e.g., Kubernetes) and secure service-to-service communication (mTLS, policy enforcement). Familiarity with zero trust, segmentation, and modern security architectures; exposure ...

pipelines for near-real-time detection (packet/flow analytics). Background in resilience engineering, chaos testing, disaster recovery, and capacity planning at hyperscale. Containerization/orchestration (e.g., Kubernetes) and secure service-to-service communication (mTLS, policy enforcement). Familiarity with zero trust, segmentation, and modern security architectures; exposure ...

pipelines for near-real-time detection (packet/flow analytics). Background in resilience engineering, chaos testing, disaster recovery, and capacity planning at hyperscale. Containerization/orchestration (e.g., Kubernetes) and secure service-to-service communication (mTLS, policy enforcement). Familiarity with zero trust, segmentation, and modern security architectures; exposure ...

pipelines for near-real-time detection (packet/flow analytics). Background in resilience engineering, chaos testing, disaster recovery, and capacity planning at hyperscale. Containerization/orchestration (e.g., Kubernetes) and secure service-to-service communication (mTLS, policy enforcement). Familiarity with zero trust, segmentation, and modern security architectures; exposure ...

pipelines for near-real-time detection (packet/flow analytics). Background in resilience engineering, chaos testing, disaster recovery, and capacity planning at hyperscale. Containerization/orchestration (e.g., Kubernetes) and secure service-to-service communication (mTLS, policy enforcement). Familiarity with zero trust, segmentation, and modern security architectures; exposure ...

pipelines for near-real-time detection (packet/flow analytics). Background in resilience engineering, chaos testing, disaster recovery, and capacity planning at hyperscale. Containerization/orchestration (e.g., Kubernetes) and secure service-to-service communication (mTLS, policy enforcement). Familiarity with zero trust, segmentation, and modern security architectures; exposure ...

pipelines for near-real-time detection (packet/flow analytics). Background in resilience engineering, chaos testing, disaster recovery, and capacity planning at hyperscale. Containerization/orchestration (e.g., Kubernetes) and secure service-to-service communication (mTLS, policy enforcement). Familiarity with zero trust, segmentation, and modern security architectures; exposure ...

pipelines for near-real-time detection (packet/flow analytics). Background in resilience engineering, chaos testing, disaster recovery, and capacity planning at hyperscale. Containerization/orchestration (e.g., Kubernetes) and secure service-to-service communication (mTLS, policy enforcement). Familiarity with zero trust, segmentation, and modern security architectures; exposure ...