I'm wondering about the difference between ML SWE and "applied scientist" tracks at a few companies. I'd like to join the teams actually applying ML, owning production code, working together, hiring and mentoring people and solving the problems. I'd like to avoid any science roles that don't touch code, have to give up ownership of their solutions and keep moving on to new domains, don't get to scale or grow a team. I'm a people person, and I'd like to work on a stable team instead of as a lone creative. At FB, ML SWE own the models and scale the teams around them; the Science teams are occasional collaborators who frequently switch problems/domains. So, SWE would be the best pick at Facebook by my criteria. From what I've heard, the same thing is true at Google (though science jobs at both companies can be prestigious/cool, they don't own the code or have much chance of tech leading / managing in a space). What about Netflix, Amazon, and Microsoft? Who owns the models and grows the teams in these companies---SWE or Science? If you could do both jobs, which would you pick? #amazon #netflix #microsoft #google
Not sure if this is the case for all Microsoft, but in my org it is similar. SWE/MLE owns the code and scale.