@darshan-majithiya had opened #15429 to add the hyperparameter tuning PR but it's gone stale. I'm adding this issue to see if they want to pick it back up, or if not, if someone wants to pick up where they left off in the spirit of open source 😄 
airflow/providers/google/cloud/example_dags/example_mlengine.py
model_name=MODEL_NAME,
        data_format="TEXT",
        input_paths=[PREDICTION_INPUT],
        output_path=PREDICTION_OUTPUT,
        labels={"job_type": "prediction"},
    )
    
    
    delete_version = MLEngineDeleteVersionOperator(
        task_id="delete-version", project_id=PROJECT_ID, model_name=MODEL_NAME, version_name="v1"
    )
    
    
    delete_model = MLEngineDeleteModelOperator(
        task_id="delete-model", project_id=PROJECT_ID, model_name=MODEL_NAME, delete_contents=True
    )
    
    training >> create_version
    training >> create_version_2
    create_model >> get_model >> [get_model_result, delete_model]
    create_model >> get_model >> delete_model
    create_model >> create_version >> create_version_2 >> set_defaults_version >> list_version
    create_version >> prediction
    create_version_2 >> prediction
    prediction >> delete_version
    list_version >> list_version_result
    list_version >> delete_version
    delete_version >> delete_model
    
    def get_metric_fn_and_keys():