- Strong programming experience in Python.
- Hands-on experience with Machine Learning workflows and MLOps.
- Strong understanding of ML lifecycle management.
- Experience with MLflow / Kubeflow / Airflow.
- Experience with CI/CD tools such as Jenkins, GitHub Actions, GitLab CI or Argo CD.
- Solid hands-on experience with Docker and Kubernetes.
- Experience with at least one cloud platform:
- AWS
- Microsoft Azure
- Google Cloud Platform
- Experience with model deployment and monitoring.
- Knowledge of model versioning, experiment tracking and model registry.
- Experience with REST APIs using FastAPI/Flask.
- Good understanding of Linux and scripting.