Many benefits of running infrastructure in the cloud are lost for offline batch processing jobs. Training machine learning models doesn't require low response times, high availability, geographic proximity to clients, etc. Yet, with cloud, you're paying for all this extra infrastructure.
The main benefits of cloud for tasks with machine learning type workloads are cost saving (if utilization is low) and no electrical set-up.
On the other hand, cloud is extremely expensive for groups that require high base levels of GPU compute. The article is arguing that such groups can save a huge amount of money by moving infrastructure on-prem.
I'd email webnx sales, they have some EPYC servers although not this very new CPU but they were always very flexible. It might be more economical if you front the price of the CPUs but the 7371 is very cheap for what it is, the two should be around $3k (I saw them as a special order on gamepc for 1600, the site name is very ironic because the monsters they sell are more workstation / server than gaming pc). I am not affiliated, just a very satisfied customer, I worked with them when I was the lead architect of a US Top 100 (per Quantcast) site.
The 1080 Ti is certainly not a problem for them.