What we would like ideally, is a system where development, training, and deployment are almost one and the same thing, to reduce the lead time from development code to production models.

This is very aligned with the goals of ClearML 🙂
I would to understand more on what is currently missing in ClearML so we can better support this approach

my inexperience in using them a lot until recently. I can see how that is a better solution

I think I failed in explaining my self, I meant instead of multiple CUDA versions installed on the same host/docker, wouldn't it make sense to just select a different out-of-the-box docker with the right CUDA, directly from the public nvidia dockerhub offering ? (This is just another argument on the Task that you can adjust), wouldn't that be easier for users?