Found Description
Key Responsibilities
- Deploy machine learning models into production environments using scalable and automated deployment practices.
- Build and maintain model serving infrastructure for real-time and batch inference use cases.
- Implement monitoring frameworks to track model performance, drift, latency, data quality and service reliability.
- Automate model retraining pipelines in collaboration with ML Engineers and Data Engineers.
- Manage model versioning, deployment lifecycle and rollback strategies.
- Operationalise CI/CD pipelines for machine learning workflows in collaboration with Platform Engineering teams.
- Ensure model deployments comply with security, governance, privacy and enterprise architecture standards.
- Support incident management, root cause analysis and resolution of model performance issues in production.
- Optimise model inference performance, scalability and cost efficiency across cloud en...