Role & responsibilities
- Design and implement enterprise-scale MLOps platforms on Azure Cloud.
- Build and manage ML model deployment architectures using Azure Kubernetes Service (AKS).
- Develop CI/CD and CT (Continuous Training) pipelines for ML workflows.
- Automate model packaging, deployment, retraining, and rollback strategies.
- Integrate Azure Machine Learning, AKS, Azure DevOps, GitHub Actions, and container technologies.
- Collaborate with Data Scientists, Data Engineers, Solution Architects, and DevOps teams.
- Implement model monitoring, drift detection, performance tracking, and alerting mechanisms.
- Ensure platform security, compliance, and governance standards.
- Optimize AKS clusters for performance, scalability, and cost efficiency.
- Establish MLOps best practices, reusable frameworks, and deployment standards.