Design, implement, and maintain MLOps pipelines for AI/ML assets deployed as managed online endpoints in Azure Machine Learning.
Implement CI/CD workflows for AI solutions using Azure DevOps and Azure CLI.
Ensure compliance, security, and scalability of AI systems across environments.
Build monitoring dashboards to track performance, data drift, and system health, and implement alerting and remediation strategies.
Manage promotion of AI/ML assets (models, apps, containers) across development, staging, and production environments.
Automate deployment, monitoring, and lifecycle management of AI systems, including Azure Speech Services and OpenAI models.
Assist in deploying and maintaining Flask-based applications that consume Azure ML endpoints.

5+ years of experience in MLOps or related roles with a focus on Azure cloud platform
Strong proficiency in Azure AI services (Azure Machine Learning, Cognitive Services, Azure Speech Services, Azure OpenAI)
Hands-on experience with CI/CD pipelines using Azure DevOps and Azure CLI
Proficiency in Python and experience with Azure SDKs for AI services
Solid understanding of containerization (Docker) and orchestration (Kubernetes, AKS)
Experience with monitoring and logging solutions for AI systems (Azure Monitor, Application Insights) and building dashboards
Knowledge of identity and access management in Azure (Managed Identity, RBAC)
Strong understanding of AI/ML asset lifecycle management, including promotion across environments.

25 days holiday, increasing through length of service, with option to buy or sell
Bupa health insurance as a benefit in kind
An enhanced pension plan and life insurance
Onsite gyms or local discounts where no onsite gym available
Various other benefits and online discounts

DevOps Engineer – ML

Key skills