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
