This is a remote position.
We are looking for a Senior DevOps ML Engineer to support a long-term enterprise AI platform focused on production-grade ML workloads. This role is fully centred on MLOps and DevOps infrastructure — ensuring that existing AI and ML models run reliably, securely, and at scale in production. The position operates in a regulated environment and requires strong focus on automation, governance, and operational excellence.
Responsibilities
- Design, build, and maintainMLOpsand DevOps infrastructure on Azure
- Develop andoptimiseML pipelines for deployment, monitoring, and governance
- Work with Azure Databricks,MLflow, and Unity Catalog
- Implement CI/CD pipelines and automatedModelOpsworkflows
- Ensure data architecture supports governance, lineage, and schema evolution
- Apply Infrastructure as Code using Terraform
- Collaborate closely with AI engineers and data teams to support production ML systems
- Monitor and ensure platform stability, performance, security, and compliance
- Support operational readiness of ML workloads in regulated environments
Requirements
- Stronghands-onexperiencewithAzureDatabricks,includingMLflowand UnityCatalog
- Proven background in DevOps orMLOpsfor AI / ML platforms
- Solid experience with Azure Cloud services
- Hands-on CI/CD and pipeline automation experience
- Infrastructure as Codeexpertiseusing Terraform
- Strong understanding of data governance, access control, and compliance principles
- Confident English for daily cooperation with international stakeholders
Nice to have
- Pythondevelopmentorscriptingexperience
- Docker and Kubernetes knowledge
- Exposure to Generative AI or broader ML workflows
- Experience working in insurance or other regulated environments
Benefits
- Solid, competitive salary
- Work in multinational environment on international projects
- Comprehensive healthcare
- Long-term B2B contract with stable project pipeline
- Fully remote model
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