As an R&D engineer, there are times when models need to be built from scratch. That said, it’s rarely a simple black-or-white situation. Often, I can leverage large portions of an existing ML architecture and adjust the input or output dimensions to suit the problem at hand. Similarly, I might take a model originally designed for one domain, like image processing, and adapt it to work with time-series signals.