ML engineer system design round at Meta, one question about building a next word prediction system. Pretty open-ended and I wasn't fully sure how deep to go on the ML side versus the infrastructure side.
“I started with the obvious stuff, n-gram models, then moved to neural approaches, but I kept second-guessing how much time to spend on model architecture versus serving latency.” The rest of the author's notes on Machine Learning Engineer interview at Meta, Onsite - System Design / Architecture round, covers how they worked through the question, what the panel pushed back on, and what they would do differently.