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Experience Required: 5–8 years
Tech Stack: Azure | Databricks | AKS | ARO | Terraform | MLflow | CI/CD
Role Summary
We are looking for a seasoned cloud engineer to support ML development teams and drive end to end automation for model deployment and operations across Azure, Databricks, and Kubernetes platforms.
Key Responsibilities
• Build and maintain CI/CD/CT pipelines for ML models using Azure DevOps / GitHub Actions/Jenkins
• Develop and manage deployment workflows for:
o Databricks Jobs
o MLflow models
o Microservices running on AKS / ARO
• Automate infrastructure using Terraform, scripting, and GitOps practices
• Manage and optimize:
o Databricks workspaces
o AKS clusters
o Networking and model serving environments
• Implement monitoring, logging, and alerting for ML systems and platform reliability
• Collaborate closely with ML engineers, data engineers, and application teams
• Ensure security best practices, governance, and cost optimization across MLOps pipelines
Required Skills
• Strong hands on experience with Azure, AKS, ARO and Databricks
• Solid experience with MLflow, Kubernetes based model deployments
• Proficiency in Python and Bash / PowerShell
• Good understanding of cloud security, networking, and distributed systems
Job ID: 148697197
Skills:
Networking, PowerShell, Veeam, Dns, DHCP, Ansible, Commvault, Microsoft Azure, Azure, Python, Virtualization, Azure DevOps, Active Directory, Data Protection Engineering, Rubrik, Azure CLI
Skills:
Bash Scripting, Python, Terraform, PowerShell, GitHub Actions, RHEL Red Hat Enterprise Linux, Google Cloud Platform GCP
Skills:
Github, Cloudformation, Artifactory, Pulumi, Devops, Jenkins, Gcp, Terraform, Sonarqube, AWS, Infrastructure as Code, MFA, Ai, Snyk, GitLab CI, LLM tools, GitHub Actions, rbac, observability tooling, SecOps
Skills:
Devops, Powershell Scripting, Automation using Cloud Native or CICD and TFE, High-Availability, Azure Cloud Platform Operations, VPN Networking, VM Storage, Azure Cloud services deployments
Skills:
identity access management, Sql, AWS Glue, DataFlow, BigQuery, Cloudformation, Dataproc, Bash, Kubernetes, Python, Terraform, Lake Formation, Managed Kafka, Omnia platform, AWS Deployment Manager, RDBMS with ANSI SQL, GKE, Vector DB, Glue Catalogue, cloud security principles, Google Data Warehouse
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