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Apple interview notes, page 8 of 38

FAANG / Big Tech

Most of these Apple write-ups come from Software Engineers (212), then Machine Learning Engineers (85) and Data Scientists (32). The most reported rounds are the technical phone screen (217), the system design round (48), the product sense round (29) and the behavioral / leadership round (22).

372 interview notes · updated Oct 2026

Apple·Machine Learning Engineer·Technical Phone Screen

Apr 2026
Apple MLE interview with a meaty open-ended question about how you'd actually build a model from scratch. One question but it covers a lot of ground, felt more like a conversation than a quiz.
  • Walk me through your full process for developing a model on a new task, from defining the problem and success metrics all the way through iteration, scaling, and deciding when to invest in data quality versus model capacity.

“This is the kind of question that sounds easy until you're actually talking and realize you're just listing buzzwords.”

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Apple·Software Engineer·Technical Phone Screen

Apr 2026
Apple SWE interview, got asked to design an iterator. Not much else to go on but it was a coding/design type question.
  • Design an iterator.

“Pretty open-ended, which I wasn't expecting.”

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Apple·Software Engineer·Technical Phone Screen

Apr 2026
Apple SWE interview with a classic stock trading problem. Nothing too wild but it required more careful thinking than I expected going in.
  • Given stock prices for each of the next n days, how do you maximize profit if you can buy or sell one share per day?

“My first instinct was to just find the global min and max and call it done.”

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Apple·Software Engineer·Onsite - System Design / Architecture

Apr 2026
Apple system design round for a software engineer role. One question, pretty focused, but it had enough layers to keep me busy for the whole session.
  • Design a high-throughput service that accepts a positive integer and determines whether repeatedly replacing it with the sum of its squared digits eventually reaches 1. The service needs to handle billions of requests efficiently, with low latency and minimal redundant computation.

“I went straight to caching and that was the right instinct, but I fumbled explaining why the cache stays small.”

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Apple·Product Manager·Onsite - Product Sense / Strategy

Apr 2026
Apple product sense question, just the one prompt about classical music on Apple Music. Short and open-ended, which sounds easy until you realize how much rope they're giving you to hang yourself with.
  • How would you design a classical music product experience within Apple Music?

“I went straight to user segmentation and probably spent too long on it.”

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Apple·Software Engineer·Technical Phone Screen

Apr 2026
Apple software engineer interview with a debugging-focused technical question. Pretty straightforward premise but the depth they wanted was more than I expected.
  • You have a Python script that hangs or gives wrong output due to a buggy loop condition. Walk through how you'd debug it systematically, including what tools you'd use and what common loop mistakes you'd look for.

“I started with the obvious stuff: print statements inside the loop to see if it's even executing, then check whether the termination condition is ever reachable.”

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Apple·Software Engineer·Technical Phone Screen

May 2026
Apple security engineer interview, one technical question about unix persistence mechanisms. Pretty sparse on details but the topic itself has a lot of depth to it.
  • What are the techniques malware uses to maintain persistence on Unix-based systems?

“This is the kind of question where you either know the landscape or you don't.”

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Apple·Data Scientist·Technical Phone Screen

May 2026
Apple data scientist interview with a heavy algorithms focus. The main problem was a subarray removal question with a bunch of follow-ups tacked on, and the whole thing felt more like a systems/algorithms round than anything data science specific.
  • Given an integer array, find the shortest contiguous subarray you can remove so that the remaining elements are non-decreasing. Return [-1,-1] if the array is already sorted. Your solution must run in O(n) time with O(1) extra space.
  • How would you adapt this solution to handle streaming input where memory is limited? What data structures would you use and what are the trade-offs?
  • Can you verify in a single pass whether a given (L, R) pair is actually the optimal solution?
  • How would you extend the solution if the target condition is strictly increasing instead of non-decreasing? What if you're allowed up to k deletions rather than a single contiguous removal?

“The prefix/suffix approach clicked for me pretty fast but i fumbled the two-pointer bridging step.”

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Apple·Software Engineer·Technical Phone Screen

May 2026
Apple SWE interview with a classic logic puzzle that sounds deceptively simple but has a pretty elegant solution once you see it. The parity trick is well-known in puzzle circles but I'd never actually had to work through it under pressure before.
  • A line of dwarves each wear a hat that is either black or white. Each dwarf can see all hats ahead of them but not their own or those behind. Starting from the back, each dwarf must announce their own hat color out loud, and everyone hears every previous announcement. They can agree on a strategy beforehand. What strategy guarantees the most correct guesses?

“I knew this type of puzzle existed but blanked on the mechanics for a minute.”

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Apple·Software Engineer·Technical Phone Screen

May 2026
Apple SWE interview with a classic recursion problem. Pretty straightforward if you know your fundamentals, but they pushed on the iterative angle which I was not fully prepared for.
  • Implement Tower of Hanoi: given three pegs and N disks stacked by size on the source peg, produce the full sequence of moves to transfer all disks to the target peg following the standard rules. Then discuss recursion depth and whether you could do it iteratively.

“The recursive solution came out fine.”

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