About GyanSys Senior Cloud Engineer - Databricks: 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. (ref:hirist.tech)