Career prospects applied research vs SWE in ML
Yes they’re very different Currently interviewing for applied research and SWE positions at FAANG. SWE are for cloud ML platforms, research scientist also on ML topics. I like both from the topics alone. Which has better career growth opportunities? Is ML research in industry a fad or will it be around in 10 years? Is it possible to transition applied research -> SWE? I have no interest in going back to academia. Scared of taking the applied research role, interest in ML research in FAANG dries up and I go back to uni to be a sad post doc Looked at Glassdoor for some roles, saw tc is higher for the applied research positions I’m interviewing for at the current levels, but what about later in career, does SWE tc grow faster/higher? Help me future proof my career Tc: 🥜 fresh-ish grad in a startup yoe: PhD + 1
Ignore Glassdoor for salaries of most kinds. For Faang use levels.fyi.
I checked, but levels doesn’t have research salaries? Only swe or data scientist
Check swe roles listed as ML/AI. Some of those will be Applied Scientist
Cloud ML platforms is mostly about development of the platform, little about ML. It will fade overtime as the cloud providers improve this feature. ML Research, on the other, has unlimited potentials. There are so many things to explore, like NAS, multimodal models, MLP, etc. I'd recommend Research Scientist if you want to be a ML expert .
Swe ml. You will always have the option to collaborate with research team if you want
Pay will be less than applied research?
And work is less related to ML algorithms?