wip mlflow implementation

README.md

@@ -73,6 +73,9 @@ To provision an MLflow tracking server, set:
 mlflow:
   mode: create
   tracking_server_name: your-tracking-server-name
+  experiment_name: qc-cli-training
+  registered_model_name: qc-cli-model
+  register_trained_models: true
 ```
 
 To use an existing MLflow tracking server, set:
@@ -83,6 +86,14 @@ mlflow:
   tracking_server_name: your-tracking-server-name
 ```
 
+Install the optional MLflow dependencies before enabling MLflow:
+
+```bash
+uv sync --extra mlflow
+```
+
+When MLflow is enabled, `train start` creates an MLflow run for the SageMaker job. `train status` finalizes that run once the job reaches a terminal state and registers completed model artifacts as pre-release model versions using the `prerelease-latest` MLflow alias.
+
 ## Commands
 
 ### `init`