5 of 5 Remote Docker Jobs in Newcastle upon Tyne

Python, or Java (Spring Boot) Solid understanding of SQL and NoSQL databases (e.g., MongoDB) Familiarity with CI/CD pipelines, Git workflows, and agile methodologies Experience with containerisation (e.g., Docker, Kubernetes) Exposure to cloud platforms (AWS preferred, Azure/GCP also valued) Nice-to-Haves: Test-driven development and automation experience Front-end integration knowledge Interest in cloud-native architecture More ❯

Have (But Not Required): University or personal project experience with cloud tools or services Exposure to Infrastructure-as-Code tools like Terraform or ARM templates Familiarity with containers (e.g., Docker, Kubernetes) Knowledge of CI/CD principles or version control systems like Git Completion of a cloud-related course or certification (e.g. AWS Academy, Azure Fundamentals) What You’ll Gain More ❯

Terraform Networking fundamentals Microsoft Azure, SCCM, Intune SQL Server, AD, ADFS Windows Server, Hyper-V Azure AD, Debugging Tools SLA & escalation management Linux RHEL, CentOS, Ubuntu Bash, Python, Ansible Docker, Kubernetes Systemd, YUM/APT CI/CD familiarity Basic & Preferred Qualifications Basic: Bachelors degree in a relevant field or equivalent combination of education and experience Typically 5+ years of More ❯

in Azure architecture, automation (Terraform, Ansible), and DevOps tooling (Azure DevOps, GitHub) Strong leadership and communication skills in a matrix-managed environment Expertise in Azure IaaS, PaaS, SaaS, containerisation (Docker, Kubernetes), and FinOps Why join us? You'll be part of a forward-thinking team, shaping the future of our infrastructure with the latest cloud technologies. If you're passionate More ❯

improve model performance Model Evaluation : Learn to test models for accuracy, robustness, and fairness using best practices Deployment : Help package and deploy ML models into production using tools like Docker, APIs, or cloud platforms Collaboration : Work closely with software engineers, data scientists, and product teams to integrate ML into real products and services Experimentation : Participate in testing new algorithms, researching … or Azure) Knowledge of software engineering best practices, version control (Git), or CI/CD pipelines Understanding of deep learning, NLP, or computer vision Familiarity with deployment tools like Docker or MLflow What You’ll Gain Hands-on Experience : Work on real ML systems and contribute to production-grade solutions Mentorship & Training : Learn from senior ML engineers and participate in More ❯