[sumodm]

My 2 cents 1. You don't need a Ph.D to build a product that uses DL/ML. Some part of your work here could be to define the problem and to understand how to phrase the problem so that it is solvable (if its too easy, your moat won't be technological). Your contribution here could be applying deep learning to new applications. Specifically for applying DL in industry, someone with ability to quickly tryout a lot of things is a good thing to have (with some amount of self-discipline). 2. You don't need a Ph.D to be part of a team that is taking on a hard DL/ML problem. You will hopefully have leaders who can set the directions. 3. Ph.D like most degrees is a label. If you can develop the skills of a good researcher (like any other craftsman), learning to comprehend research ideas quickly, keeping tab of interesting ideas and recent progress, then one could easily find connections and even publish good papers. 4. Now if you really want to understand what happens deep down, why does DL work, to understand how it could be viewed as Tensor Decomposition or coming up with new mathematical optimization or drawing a new connection between sub-areas: then having dedicated time to build those skill-sets (aka Ph.D) is very helpful.