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.

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