Hi all,

I have a couple of interviews coming up for research scientist roles with FAANG-like companies and since it’s my first time going through this process (finishing grad school, never applied to industry positions before) I was wondering how the interviews are conducted and what they look at the most. I can find tons of information on the recruitment process for SWE at big N companies, and how you have to grind leetcode for months to pass the coding bar, but not much info on the more research oriented roles. Do they have the same bar for coding? Do they put more emphasis on your performance during the ML and design interviews? What “signal” do they look for, presumably outside of your research portfolio, which they’d know already by the time you come for an onsite?

Finally, in case anyone here works at a the research groups in major tech companies, what’s been in your experience the interview:offer ratio, is it as bad as for developer roles (I read that for Google it is about 1:7)? I would imagine that for research roles, it is easier to see if there is a good fit on data outside of algo&ds / design interview performance, like research interests and publication record, but maybe I am naive.

Sorry for the many questions, just a scared grad student trying to understand what his chances are 😀

Thanks.