@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 😄 
tests/providers/google/cloud/operators/test_mlengine.py
request = {
            'jobId': 'test_training',
            'trainingInput': {
                'region': 'europe-west1',
                'scaleTier': 'CUSTOM',
                'masterType': 'n1-standard-8',
                'masterConfig': {
                    'imageUri': 'eu.gcr.io/test-project/test-image:test-version',
                },
            },
        }
        response = request.copy()
        response['state'] = 'SUCCEEDED'
        hook_instance = hook.return_value
        hook_instance.create_job.return_value = response
        operator = MLEngineStartTrainingJobOperator(**arguments)
        operator.execute(MagicMock())
        hook.assert_called_once_with(
            gcp_conn_id='google_cloud_default',
            delegate_to=None,
            impersonation_chain=None,
        )
        assert len(hook_instance.mock_calls) == 1
        hook_instance.create_job.assert_called_once_with(
            project_id='test-project',
            job=request,
            use_existing_job_fn=ANY,
        )
    @patch('airflow.providers.google.cloud.operators.mlengine.MLEngineHook')
    def test_success_create_training_job_with_optional_args(self, mock_hook):