I should say, the company I am working Malvern Panalytical, we are developing an internal MLOps capability, and we are starting to develop a containerized deployment system, for developing, training and deploying machine learning models. Right now we are at the early stages of development, and our current solution is based on using Azure MLOps, which I personally find very clunky.

So I have been tasked with investigating alternatives to replace the training and model deployment side of things.

The likely solution will involve the use of Prefect for containerized pipelines, and then interfacing with various systems, for example, ClearML, for better handling of model development, training and deployment.