Job Description

Job Summary

We are seeking a skilled and motivated DevOps Engineer to join our dynamic team. The ideal candidate will play a pivotal role in enhancing our software development processes and ensuring the reliability of our cloud infrastructure. You will collaborate closely with development and operations teams to streamline deployment, improve system performance, and implement best practices in continuous integration and delivery.

Duties

Design and deploy Azure ML infrastructure -- including workspaces, compute clusters, storage accounts, and networking -- using Terraform or Bicep for fully automated provisioning. Automate deployment processes using technologies like Docker, Kubernetes, Terraform, and Ansible. Monitor system performance and troubleshoot issues using tools such as New Relic, Splunk, and Elasticsearch. Collaborate with software development teams to ensure seamless integration of new features and enhancements. Implement disaster recovery strategies to ensure business continuity. Maintain system security through effective firewall management and incident response protocols. Conduct system testing and quality assurance to ensure software reliability. Manage version control systems using GitHub or GitLab for efficient code collaboration. Participate in requirements gathering sessions to understand project needs and deliver solutions accordingly.

Requirements

Design and deploy Azure ML infrastructure -- including workspaces, compute clusters, storage accounts, and networking -- using Terraform or Bicep for fully automated provisioning. Develop CI/CD pipelines in Azure DevOps for end-to-end ML workflows -- covering data ingestion, model packaging, deployment, and monitoring stages. Implement secure connectivity and governance by integrating private endpoints, managed identities, and Key Vaults into all ML environments. Orchestrate scalable training and inference workloads on Azure Kubernetes Service (AKS), enabling GPU/CPU optimization and autoscaling for cost efficiency. Integrate data processing pipelines using Azure Data Factory, Synapse, and Event Hub to support large-scale ML data preparation and feature engineering. Enable observability and reliability by configuring centralized monitoring with Azure Monitor, Log Analytics, and Application Insights for both infrastructure and ML assets. Collaborate with data scientists and ML engineers to productionize models in a standardized, reproducible, and auditable environment. Familiarity with CI/CD pipelines using Jenkins or similar tools for automated software deployment. Ability to work in UNIX/Linux environments; knowledge of shell scripting is advantageous. Strong problem-solving skills with a focus on debugging and troubleshooting software issues. Join us as we innovate and optimise our DevOps practices while delivering high-quality software solutions!
Job Type: Full-time

Pay: 35,000.00 per year

Work Location: In person