What does A MLOps Engineer do?
A MLOps Engineer is responsible for building and maintaining ML training and inference pipelines, model deployment workflows, and monitoring infrastructure using MLflow, Kubeflow, and Azure ML to productionise machine learning at scale.
Day-to-day responsibilities
- Designing and maintaining ML training and inference pipelines
- Building CI/CD workflows for model deployment with MLflow
- Kubeflow
- Azure ML
- Monitoring model performance and data drift in production
- Collaborating with data scientists to productionise experimental models
Very High demand+18% MLflow or Kubeflow ML pipeline tools+16% Kubernetes and container orchestration+14% Python ML engineering