Senior Cloud Engineer MLOps & Azure (5 8 Years)

About the Role We are looking for a Senior Cloud Engineer with 5–8 years of experience in cloud infrastructure, MLOps, and automation to support ML development teams and build scalable, production-ready AI/ML platforms. The ideal candidate will have hands-on experience with Azure, Databricks, Kubernetes, and CI/CD pipelines to drive end-to-end automation for model deployment and operations across cloud-native environments. Experience: 5–8 Years Employment Type: Full-Time Location: Bengaluru (Onsite) Key Responsibilities Build and maintain CI/CD/CT pipelines for ML models using Azure DevOps, GitHub Actions, and Jenkins. Develop and manage deployment workflows for Databricks Jobs, MLflow models, and microservices running on AKS and ARO. Automate infrastructure provisioning using Terraform, scripting, and GitOps best practices. Manage and optimize Databricks workspaces, AKS clusters, networking, and model-serving environments. Implement monitoring, logging, and alerting mechanisms to ensure platform reliability and performance. Collaborate with ML Engineers, Data Engineers, and application teams to build scalable MLOps solutions. Ensure cloud security, governance, and cost optimization across ML deployment pipelines. Required Skills & Qualifications 5–8 years of experience in Cloud Engineering, MLOps, or related domains. Strong hands-on experience with Azure, Databricks, AKS, and ARO. Experience with MLflow and Kubernetes-based model deployments. Proficiency in Python and Bash/PowerShell scripting. Strong understanding of CI/CD pipelines and infrastructure automation using Terraform. Good understanding of cloud security, networking, and distributed systems. Experience working with containerized and cloud-native applications. Preferred Skills Exposure to GitOps practices and infrastructure-as-code methodologies. Experience with monitoring, logging, and observability tools for cloud platforms. Strong analytical, problem-solving, and collaboration skills