Training with a custom service account needs a new field named service account
trainingInput:
  serviceAccount: CUSTOM_SERVICE_ACCOUNT

https://cloud.google.com/ai-platform/training/docs/custom-service-account


airflow/providers/google/cloud/operators/mlengine.py
"""
    Start a Google Cloud ML Engine prediction job.
    .. seealso::
        For more information on how to use this operator, take a look at the guide:
        :ref:`howto/operator:MLEngineStartBatchPredictionJobOperator`
    NOTE: For model origin, users should consider exactly one from the
    three options below:
    1. Populate ``uri`` field only, which should be a GCS location that
       points to a tensorflow savedModel directory.
    2. Populate ``model_name`` field only, which refers to an existing
       model, and the default version of the model will be used.
    3. Populate both ``model_name`` and ``version_name`` fields, which
       refers to a specific version of a specific model.