From my experience (and what this looks like) is that there isn't a ton of novel IP to open source here. A lot of the times ML "platforms" are composed of a number of open source components glued together in an elegant way (which I'm not implying is easy, because it's very difficult).

From looking at this from the outside the only things in this platform that may be open-sourceable would be the job scheduling and visualizations - and there are already variants of open source tooling which could be repurposed for those tasks (or may even be powering those components).

The main purpose of this post seems to be Uber's way of standardizing their workflows + a little extra glue (which they're calling their platform). It still provides a lot of value. Also, Uber does have a few cool open source projects: https://uber.github.io/ (but could admittedly have more).