Senior MLOps Engineer – Azure, Databricks & Kubernetes

About the Role

We are looking for a hands-on Senior MLOps Engineer with strong experience in Azure, Databricks, MLflow, and Kubernetes-based deployments. This role is focused on building and automating end-to-end ML deployment pipelines, managing AI/ML infrastructure, and enabling ML teams to deploy models reliably at scale.

This is not a traditional DevOps or Cloud Operations role. We are specifically looking for professionals who have worked closely with Data Science and Machine Learning teams to operationalize ML models in production environments.

What You'll Be Doing

• Design, build and maintain CI/CD/CT pipelines for Machine Learning workloads.
• Automate deployment of MLflow models and Databricks workloads.
• Deploy and manage AI/ML services on AKS and OpenShift (ARO).
• Build Infrastructure-as-Code using Terraform.
• Implement monitoring, logging, observability, and governance for ML platforms.
• Collaborate with ML Engineers, Data Scientists, and Data Engineers to productionize models.
• Optimize Azure-based AI infrastructure for scalability, security, and cost efficiency.
• Support enterprise-scale AI and Agentic AI initiatives.

Please Apply Only If You Have

• Hands-on Databricks experience
• Built CI/CD pipelines for ML workloads
• Worked with Azure Kubernetes Services (AKS)
• Experience deploying MLflow models in production
• Terraform-based infrastructure automation experience

Applications without Azure + Databricks + MLOps experience are unlikely to be considered.