I have a machine learning engineer interview coming up at Apple for ICT4 and one of the topics I need to prep on is “machine learning platform knowledge, large scale distributed system knowledge” I was wondering if anyone could shed some insight into what they think this interviewer would ask. Like specific technologies? Overall workflow of deploying machine learning models? TC: 160k #software #engineering #machinelearning #ml
mix of things. sample problems could be like "design recommendation system for Amazon" or "how will you extract out features from tiktok videos which will later be fed into model for inference" depending on interviewer, they can go deeper into Modeling side or infra side. at modeling side, they can ask to design features, architecture for models, extracting dataset. at infra side, they'll look for production deployment, like monitoring, how well you test that it's ready for production before its up there, what will you do if prediction fails, what's the baseline model
Get the book machine learning design patterns. That will cover 90% of what you need
Depends on the company and level. Is it at Meta? E5?
Apple ICT4