>I did not get the position, but I would recommend you look elsewhere if your focus is truly machine learning
For ML, it's really important to join a team where your interests in ML are aligned with what the team does. It's really hard to see this from a job description. There's enough going on at Google that you can find work that fits.
I've interviewed twice at Google and had the same experience as you. No ML or math questions at all. More algorithms and how to quantify a business problem. That being said, I asked enough questions to realize that some groups use ML, but that's a small part of what they are doing. For example, they might have a platform for doing A/B testing and the "Data Scientist" job is really defining A and B and feeding that into the platform to extract metrics. How much ML being done is going to be different on the Ads team than a customer facing services role for Google Cloud.
I had similar experiences interviewing at Facebook, just with more probability and stats brain teasers. Facebook doesn't guarantee which job you'll get once you're in. You go to the bootcamp and then which team you end up is decided after the bootcamp. That doesn't work for everybody if there are certain types of ML work you're not interested in.
