@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/operators/mlengine.py
"""
    Creates a new version in the model
    .. seealso::
        For more information on how to use this operator, take a look at the guide:
        :ref:`howto/operator:MLEngineCreateVersionOperator`
    Model should be specified by `model_name`, in which case the `version` parameter should contain all the
    information to create that version
    :param model_name: The name of the Google Cloud ML Engine model that the version belongs to. (templated)
    :type model_name: str
    :param version: A dictionary containing the information about the version. (templated)
    :type version: dict
    :param project_id: The Google Cloud project name to which MLEngine model belongs.
        If set to None or missing, the default project_id from the Google Cloud connection is used.
        (templated)
    :type project_id: str
    :param gcp_conn_id: The connection ID to use when fetching connection info.
    :type gcp_conn_id: str
    :param delegate_to: The account to impersonate using domain-wide delegation of authority,
        if any. For this to work, the service account making the request must have
        domain-wide delegation enabled.
    :type delegate_to: str
    :param impersonation_chain: Optional service account to impersonate using short-term
        credentials, or chained list of accounts required to get the access_token
        of the last account in the list, which will be impersonated in the request.
        If set as a string, the account must grant the originating account
        the Service Account Token Creator IAM role.
        If set as a sequence, the identities from the list must grant