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Apple interview notes, page 33 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

Jun 2026
Apple ML Engineer interview with a string pattern matching problem that sounds deceptively simple until you realize they want you to handle overlapping matches efficiently. The note about avoiding quadratic time is doing a lot of heavy lifting there.
  • Write a generator that scans a string and yields True once for each occurrence of a given pattern, including overlapping matches, without using a naive quadratic approach.

“The overlapping part is what gets you.”

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Apple·Machine Learning Engineer·Onsite - System Design / Architecture

Jun 2026
Apple ML engineer virtual onsite, second round was a system design focused on building a chatbot. Pretty standard for the role but it required more depth than I expected.
  • Design an ML-powered chatbot system end to end.

“This one sprawled in every direction fast.”

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Apple·Machine Learning Engineer·Technical Phone Screen

Jul 2026
Apple ML interview, one question about model evaluation metrics. Not much else to go on but it's the kind of question that sounds easy until you're actually in it.
  • What metrics would you use to evaluate your model's performance?

“I went straight to accuracy and then kind of rambled into precision and recall without really anchoring it to a use case first.”

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Apple·Software Engineer·Technical Phone Screen

Jul 2026
Apple coding interview for a software engineer role. One implementation problem, pretty focused session. They seem to like asking you to build data structures from scratch rather than just use them.
  • Implement a Trie (prefix tree) data structure with insert, search, and startsWith operations.

“Knew what a trie was but blanked on the clean way to structure the node class.”

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Apple·Machine Learning Engineer·Onsite - System Design / Architecture

Jul 2026
Apple ML Engineer interview that went deep into image processing optimization for mobile and embedded hardware. One question but it sprawled into a lot of sub-topics fast, which I wasn't fully ready for.
  • How would you optimize an image filtering pipeline for a resource-constrained device like a mobile phone or embedded system, where latency, memory, and power all matter?

“This question is deceptively wide.”

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Apple·Software Engineer·Technical Phone Screen

Jul 2026
Interviewed for a security engineer role at Apple and got asked a pretty foundational question about pen testing. Short round, felt more like a screen than a deep technical dive.
  • What is penetration testing and why is it necessary?

“Pretty baseline question but I still fumbled the 'why' part a bit.”

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Apple·Software Engineer·Technical Phone Screen

Jul 2026
Apple SWE coding round with a filesystem path problem. The hint about using a stack was actually embedded in the problem itself which felt a little generous, but the implementation details still tripped me up.
  • Given a string representation of a file system where entries are separated by newlines and tab characters indicate directory depth, return the length of the longest absolute path to a file. Return 0 if no files exist.

“I parsed the depth fine using the tab count but then fumbled on tracking cumulative path lengths per depth level.”

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Apple·Software Engineer·Hiring Manager Screen

Jul 2026
Behavioral screen for a software engineer role at Apple. Two questions, nothing too wild, but the deadline one took me a second to land on a good story.
  • Walk me through your career history.
  • Tell me about a time you had to work under a tight deadline.

“Pretty standard opener.”

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Apple·Machine Learning Engineer·Technical Phone Screen

Jul 2026
Apple ML Engineer coding round with two algorithm problems. Pretty standard stuff but they wanted full complexity analysis on both, which I wasn't fully prepared for.
  • Given an array of daily stock prices, find the maximum profit from a single buy-sell transaction. Return 0 if no profit is possible. Explain your algorithm and analyze time and space complexity.
  • Given piles of bananas and a time limit in hours, find the minimum integer eating speed that allows finishing all piles in time. Each hour the monkey eats from one pile only. Explain your approach and complexity.

“Classic sliding window / greedy thing.”

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Apple·Software Engineer·Technical Phone Screen

Jul 2026
Apple interview focused on predicting harmful text. Not a lot to go on from what was shared, but it reads like a machine learning or trust and safety type role with a content moderation angle.
  • How would you build a system to predict whether a piece of text is harmful?

“This is a deceptively open question.”

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