[catlover76]

I am learning about this stuff right now as well (and fortunate to be in a job where I basically get to start building this stuff with 0 credentials). I am not sure C++ and deep Nvidia Cuda stuff matter, but we are probably just thinking of different things when we say or hear "ML infrastructure".

I think of MLOps--deploying, training, managing, scaling ML systems on SageMaker, models on Bedrock, etc. Dealing with data ingestion/ETL for those systems. Managing costs. Doing SRE stuff for those systems. Stuff like that.

[minzi]

That stuff is definitely interesting! I’m thinking more about getting involved in things like PyTorch DDP and the internal equivalents I’m sure many companies massive scale companies are developing. Perhaps ML infrastructure is not exactly the right term for that…