Senior Cloud Engineer - Databricks/MLOps
First seen by Alion on Oct 15, 2026.
Senior Cloud Engineer - Databricks :
About GyanSys :
GyanSys is a global mid-tier systems integrator with over 20 years of experience, headquartered in the United States. With 3,000+ employees across 12 countries, the company serves 160+ active enterprise customers across manufacturing, industrial, consumer, life sciences, and high-tech industries.
GyanSys delivers digital transformation services leveraging SAP, Salesforce, Databricks, Snowflake, application modernization, and AI technologies.
Job Description :
We are looking for a Senior Cloud Engineer - Databricks / MLOps with strong hands-on experience in Microsoft Azure, Databricks, Kubernetes, and MLOps. The ideal candidate will support machine learning development teams by building scalable cloud infrastructure and automating end-to-end model deployment, integration, and operational workflows.
Key Responsibilities :
- Build and maintain CI/CD and CT pipelines for machine learning models using Azure DevOps, GitHub Actions, or Jenkins.
- Develop deployment workflows for Databricks Jobs, MLflow models, and microservices.
- Deploy, manage, and optimize workloads on Azure Kubernetes Service (AKS) and Azure Red Hat OpenShift (ARO).
- Automate cloud infrastructure provisioning and management using Terraform, scripting, and GitOps practices.
- Manage and optimize Azure Databricks workspaces and Kubernetes clusters.
- Configure networking and model-serving environments for scalable ML workloads.
- Implement monitoring, logging, and alerting for cloud infrastructure and MLOps platforms.
- Collaborate with ML Engineers, Data Engineers, and Application Development teams to streamline model deployment and operations.
- Ensure cloud security, governance, performance, and cost optimization across MLOps pipelines.
Required Skills :
- 5 - 8 years of experience in cloud engineering, DevOps, platform engineering, or related roles.
- Strong hands-on experience with Microsoft Azure, AKS, ARO, and Databricks.
- Practical experience with MLflow and Kubernetes-based model deployments.
- Strong understanding of MLOps, model deployment, and ML platform operations.
- Proficiency in Python and Bash or PowerShell scripting.
- Experience with Terraform, GitOps, and CI/CD automation.
- Good understanding of cloud security, networking, and distributed systems.
- Ability to collaborate effectively with cross-functional engineering teams.
Skills
MLOps, DevOps, Azure, Databricks, Kubernetes, Terraform, Python, CI/CD