Job description
Automate the lifecycle of AI systems from experimentation to production in a controlled, auditable manner.
Key Responsibilities
- Implement CI/CD pipelines for models, prompts, and agents
- Manage model versioning, rollback, A/B testing
- Build IaC for AI infrastructure (GPU clusters, endpoints, policies)
- Enable continuous training pipelines (especially for network and churn models)
- Ensure reproducibility and audit ability of models Requirements
- CI/CD tools (Jenkins, GitHub Actions, GitLab CI)
- MLOps frameworks (MLflow, Kubeflow, Airflow)
- Terraform / IaC, Docker, Kubernetes
- Monitoring tools (Prometheus, Grafana) Benefits
- Deployment frequency
- Model rollback time
- Experiment-to-production cycle time