Machine Learning Engineer Coding & Algorithms Interview Questions
Machine Learning Engineer candidates face the same data-structure bar as a backend hire, and these 319 questions are the evidence: constant-time insert, remove and uniform random sampling from a single container; an in-memory database whose insert and delete semantics you have to pin down yourself; inferring the smallest valid character ordering from sorted hints, which is a topological sort wearing a password puzzle; exclusive function times reconstructed from a call log; counting sawtooth subarrays and maximising a grid-path expression. Hash map plus array tricks, monotonic stacks, sliding windows for a moving average and grid dynamic programming carry most of the set, with no modelling content anywhere in the round. Meta accounts for 58 and OpenAI for 18, which is why so many are phrased as clarify-the-spec problems rather than textbook restatements. The round placement is unusual too: 147 were asked onsite against 144 in a technical screen, so the loop keeps testing algorithms well after the screen is passed. 275 open in a console covering Python, Java, C++ and JavaScript, and 59% are readable without a premium account.
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