Offers: Microsoft vs Twitter vs Chime

Currently working at Microsoft, 1 yoe. Staying on my current team is out of the question, although the excellent wlb gave me time to LMAO (Leetcode My A** Off). I tried internal transfer, but I have to go through an interview loop for each team. So I decided to look internally as well as externally. Current TC: 119k base + 190k stock (appreciation) + 50k signing = 166k/year after first year (in Seattle area) Offers: Microsoft, Applied Scientist, Azure AI Platform - same TC - a very hyped-up team at Microsoft - seems like I can learn a lot about cloud, distributed training, etc, on this team - terrible oncallllll and poor wlb Microsoft, Applied Scientist, Bing Ads - same TC - working on state of the art tech. But it's Bing. - I heard the working pressure is quite high, and you don't get compensated for it (except for you learn more, I guess) Twitter, Machine Learning Engineer, Consumer Product team Bay Area 135k base + 160k stock + 20k signing == 175k/year after first year - heard from a friend that the culture is like bro culture (not sure if true?) - this team is not in Cortex, is there a disadvantage? - Twitter seems like a relatively matured company, like Microsoft, is there is too much big company bureaucracy/red tape at Twitter? Chime, Software Engineer, ML Platform team Bay Area 130k base + 180k RSU + no signing == 175k / year - company has chance to IPO soon, so more $$$? - seems like their AI platform is still in development, probably more chances to do exciting work here. - startup culture can be hit or miss, not sure about culture, wlb, job stability. Questions - Is it really worth moving from Seattle to Bay Area for a rather small bump in TC for Twitter or Chime? - I heard other companies give higher bonus/refreshers than Microsoft, how much higher? Edit: since I got a DM, here is my interview prep - Skimmed cracking the coding interview ( I have read it 1 year ago, so mostly just refreshing concepts in my head) - Leetcode: I followed the problem list from 花花酱. Afterwards, brushed around 80 medium + high freq hard questions - I read DDIA (system design book) twice. I also joined an internal system design study group at Microsoft, which helped me to deepen my knowledge - For ML rounds: I read ESL (Elements of Statistical Learning). Skipped over most of the mathematical proofs - I had learned some deep learning in school and listed some projects on my resume, I watched MIT's 6.S191 course lecture vids on Youtube to review. But probably 98% of the content is irrelevant for interviews. It's only in case the interviewer asks you a deep learning trivia question. - For mock interviews, I joined an internal dl at Microsoft, and had a few mocks every week To get the interviews, mainly I reached out to some former classmates working at those companies.