I'm trying to decide between ML PhD at 5-10 CS school (in USA) and RE at FAANG (It is one of the applied teams and not pure research teams like FAIR/Google Brain)<p>If going to industry is eventual goal, which of these two options is preferable?<p>ML PhD - Highly reputed but takes 5 years to finish. Not sure if the effort + wait is worth the reward.
RE - Might not be cutting edge work. Focus is still on the product, but get to do decent amount of engineering + research for the product.<p>Eventually, I'd love to work in places like DeepMind, or AI applications like AI for drug discovery, AI for Climate Change, etc.<p>Towards this, is it beneficial to do a 5 year PhD or start from MLE/RE and graduate my way there? Really confused as to how to make this decision.<p>Thanks!
once you’re in research in a faang, it seems much easier to stay within research. teams have an easier time filling head count from within the company than externally, so transfers are common, and encouraged. getting your foot in the door there could mean you’re in a much better position to join a team on another applied project that you care about. one caveat might be: if you’re heart is set on inventing something totally novel, or without any potential product basis, then grad school is your best bet.