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-person collaboration while offering flexibility to support wellbeing, productivity, individual work styles, and life circumstances. We’re committed to fostering an inclusive environment where everyone can thrive.
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