Yes. Here is some simple code that reproduces the issue:

import argparse
from datetime import datetime

import clearml


def train(args):
    print(f"Running training: {args}")


def test(args):
    print(f"Running testing: {args}")


def parse_args():
    parser = argparse.ArgumentParser()
    subparser = parser.add_subparsers(dest="subparser")

    train_parser = subparser.add_parser("train")
    train_parser.add_argument("project", type=str)
    train_parser.add_argument("queue", type=str)
    train_parser.add_argument("--epochs", type=int)

    test_parser = subparser.add_parser("test")
    test_parser.add_argument("model_path", type=str)
    test_parser.add_argument("--metric", type=str)

    args = parser.parse_args()
    return args


if __name__ == "__main__":
    args = parse_args()
    print(args)

    task = clearml.Task.init(args.project, datetime.now().strftime("%Y%m%d-%H%M%S"))
    task.execute_remotely(queue_name=args.queue)

    if args.subparser == "train":
        train(args)
    elif args.subparser == "test":
        test(args)
    else:
        raise ValueError(f"Invalid args: {args}")

Locally it prints: Namespace(subparser='train', project='my-clearml-project', queue='worker-queue', epochs=2)
In the remote console: Namespace(subparser="['train', 'my-clearml-project', 'worker-queue', '--epochs', '2']", project='my-clearml-project', queue='worker-queue', epochs=2)