I had 5 rounds instead of 4 because I skipped phone screen, but I was pretty sure at least 3 of my interviewers didn't even look at my resume before the interviews haha.
I also did a lot of interviews for Google when I was there, and I can totally see why that's the way it is, but at least I tried to see each interviewee as a person with their own unique experience and I made sure to at least read the highlights of their resume beforehand.
Do you not feel any of the twist in your stomach that I feel when reading your post? That we're discarding any vestige of track record and accomplishment (that I pragmatically see as having correlated better than any other variable with effective coworkers in the past) for a readily gamable trivia question that I take some perverse pride in not having wasted time studying over the last decade? (Personally, I've spent my time doing far more actionable and applicable things such as running large distributed systems and learning how to do so more effectively while developing better patterns in that scope)
To be clear, this is not some defense of bias. This is a statement that your stated approach seems to throw the baby out with the bathwater. If I think to myself of what this interview process incentivises, it's not behavior that would lead me to be the engineer I am today, nor the behavior that I would chose in a coworker.
I'm just curious as to if there's any amount of dissonance inside G any more as to whether this is an effective way to get the people they want. Maybe it is, per their constant trumpeting of data driven hiring, and that's probably a great signal of why I didn't really feel at home there.
It's not your job as one of the five interviewers at Google to evaluate anything except the candidate's performance in your interview. The Hiring Committee (HC) then takes the feedback received from all the interviewers and combines it with the interviewee's résumé, any recommendations they've received, etc.
Source: gave over 100 interviews at Google.
It is impossible to give every candidate an unbiased fair chance without throwing the baby out with the bathwater.
I always pondered about that when I was at Google. We had mostly smart people, but I argue not all of them were the perfect fit for the position/skills needed.
Sure some bias are best eliminated such as what school they went to, but if work experience in general should not be discarded completely in my opinion and you can only get so much out of standard algo/DS questions, especially considering these days everyone is studying for those like standardized tests.
I literally know some CS students who just did hundreds and hundreds of practice problems and they'd ace most big company algo interviews but that doesn't really tell me if they'd be good engineers in practice at all.
He says they have to fire guys in his team frequently because they ace the interview process by practicing it ad nauseum but are terrible software engineers.
As a current student studying CS, I find all of this “leetcoding” disheartening since it unnecessarily takes away time and deprives some people of passion.
