Job description
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
Originally posted on Himalayas
Who can apply
Eligible countries: United States. Accepted UTC offsets: UTC-10, UTC-9, UTC-8, UTC-7, UTC-6, UTC-5, UTC+14. Review the full description for employer-specific work authorization, residency and schedule requirements.