The first step is a hacker rank coding challenge which you can do in Python. Then there is a technical phone interview, and then a behavioral interview with a different person. The technical interview was around an hour, and the behavioral half hour.

Initial call with recruiter, standard recruiter screen. My initial recruiter was awesome, the second one I was passed on to, not so much, I was very much a name on a screen at that point. Technical phone screen, one programming question and then a barrage of ML theory and probability questions. Then virtual on-site which was 5.5 (they cut lunch to a 30 mins Q & A so you aren't eating on camera) rounds/hours including; coding, 'data coding', data product design, ML theory, HM. Overall it was a pretty terrible experience. The prep material and reality of interview content did not align well. My very first interview the interviewer was 15 minutes late due to a technical mishap, instead of rescheduling that portion they forced to go ahead which sucked (coding round with additional stress) and really set the tone for the rest of the interviews. Overall the interviews were average difficulty but were quite different from expectations set by the prep material and also by the industry standards. I'm talking some really elementary questions but lack of prep in those areas (because they weren't listed in prep guide / aren't commonly asked in standard MLE interviews). It felt like most interviewers wanted you to fail, which was also really demotivating/disappointing. There's also this weird notion between data mining and AI, which is honestly just confusing for candidates and there should be more clarity provided to candidates. One positive was the HM round, the HM was nice and was able to have a good conversation.