AzureMLOpsEngineer

**Job Description:** **Azure MLOps Engineer** **Location: Pan India** **Required Skills and Experience:** * 5+ years of experience in ML/AI/DevOps engineering, including Edge deployment. * Strong proficiency in **OpenShift** , **Azure ML** , and **Terraform**. * Hands-on experience with **Kafka** , **Snowflake** , and **Function Apps**. * Proven experience with **CI/CD pipelines** , preferably **Azure DevOps** and **Argo**. * Good understanding of monitoring tools (**Prometheus** , **Grafana** , **AppInsights**). * Experience in secure deployments and managing **private endpoints** in Azure. **Key Responsibilities:** * **Model Deployment & Management:** * Deploy and manage ML models on **OpenShift** as REST APIs with real-time managed endpoints. * Utilize **Microsoft Azure ML** for experimentation, model training, versioning, and lifecycle management. * Configure **private endpoints** and **security protocols** for compliance and data protection. * **Data Integration & Orchestration:** * Integrate with **Snowflake** for scalable data storage and retrieval. * Use **Azure Data Factory (ADF)** and **Function Apps** for orchestrating and transforming data pipelines. * **Streaming & Messaging:** * Work with **Confluent Kafka** for real-time streaming and event-driven architectures at the edge and cloud. * **Infrastructure as Code:** * Automate infrastructure provisioning using **Terraform** for consistent deployments across environments. * **Observability & Monitoring:** * Implement observability using **Managed Prometheus** , **Grafana** , **Azure Application Insights** , and **AppInsights** for edge health, performance, and usage metrics. * **DevOps & MLOps:** * Maintain CI/CD pipelines using **Azure DevOps** and **ArgoCD** for seamless model and infrastructure delivery. * Monitor model performance post-deployment and handle model retraining as needed. At DXC Technology, we believe strong connections and community are key to our success. Our work model prioritizes in-p