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Apple interview notes, page 20 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·Software Engineer·Technical Phone Screen

May 2026
Apple AI/ML team phone screen, got LC 642 and passed through to a virtual onsite.
  • Design a search autocomplete system that returns the top k most searched historical queries for a given prefix.

“Classic trie problem but the ranking twist is where it gets interesting.”

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Apple·Software Engineer·Technical Phone Screen

May 2026
Apple SWE interview focused heavily on graph fundamentals, specifically DFS on large undirected graphs. The depth of follow-up questions caught me off guard and it went well beyond just writing the algorithm.
  • Given an undirected graph with up to 200,000 nodes and an edge list, implement DFS to find both the number of connected components and the size of the largest component.
  • Walk through both a recursive and an iterative implementation of DFS. What are the tradeoffs between them?
  • For graphs with up to 200,000 nodes, how do you handle stack overflow risk in a recursive DFS? What's your approach to making it safe?
  • What are the time and space complexities of your DFS solution, and how does the choice of graph representation affect them?
  • How would you test this implementation? What edge cases would you cover?

“I jumped straight into the recursive version and it felt clean.”

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Apple·Software Engineer·Technical Phone Screen

May 2026
Apple SWE interview with a greedy algorithm problem that looks deceptively clean on paper but has a lot of moving parts when you actually try to implement it efficiently. One question, but it had multiple layers they kept pushing on.
  • You start with some initial capital W and can complete at most K projects. Each project has a minimum capital requirement and a profit value. You can only start a project if your current funds meet its requirement, and completing it adds the profit to your funds. Design an efficient algorithm to maximize your final capital, including data structure choices, time and space complexity analysis, correctness justification, and how it scales to N around 200,000.

“I got the greedy intuition pretty fast: always pick the highest-profit available project.”

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Apple·Machine Learning Engineer·Technical Phone Screen

May 2026
Apple ML Engineer technical screen, basically one big coding question the whole time. They wanted a full K-Means implementation from scratch, no shortcuts, and expected you to talk through the messy parts too.
  • Implement K-Means clustering from scratch in Python using only NumPy. Given a 2D array of shape (n, d) and an integer k, return the final centroids and a label array. Cover initialization, the assignment and update loop, convergence, and how you'd handle edge cases like empty clusters.

“I went with k-means++ initialization because I figured random init would invite a follow-up about why I didn't.”

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Apple·Machine Learning Engineer·Technical Phone Screen

May 2026
Apple ML engineer round, one meaty coding problem centered on image processing. Not a lot of fluff, they just dropped the problem and expected you to run with it.
  • Implement a 2D image convolution filter from scratch. Given an image (grayscale or RGB) and a kernel of arbitrary size, apply the kernel at every pixel and return a filtered image of the same dimensions. Handle boundary pixels and discuss complexity and potential optimizations.

“I started with the naive nested loop approach, which is fine, but I spent too long on the boundary padding discussion before writing any code.”

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Apple·Software Engineer·Onsite - System Design / Architecture

May 2026
System design round at Apple for a software engineer role, focused entirely on building a centralized logging system from scratch. The interviewer pushed hard on four specific areas and the follow-ups got pretty deep into trade-offs I wasn't fully prepared for.
  • Design a centralized logging system that collects logs from thousands of microservice instances, stores them durably, and makes them searchable within seconds of emission.
  • How would you design the ingestion pipeline so logs get into the system reliably without impacting the services producing them?
  • How would you design the storage layer to keep logs cheap to retain but still fast to search?
  • Is exactly-once delivery worth the engineering cost for a logging system, or is at-least-once with deduplication good enough?
  • How would you handle multi-line log entries like stack traces, especially when the pipeline also sees a mix of structured JSON and plain text?
  • How would you add near-real-time alerting on log patterns, like detecting a sudden spike in error rate?
  • How would you run this logging system across multiple regions, ingesting locally but supporting global queries?

“This was the main question and it ate up most of the session.”

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Apple·Software Engineer·Technical Phone Screen

May 2026
Apple SWE interview with a classic recursion problem that feels deceptively simple until you have to explain the complexity out loud. Pretty standard technical screen vibe.
  • Given n disks stacked on peg A by size (largest at bottom), write a program to move all disks to peg C using peg B as auxiliary, moving one disk at a time and never placing a larger disk on a smaller one. Define your move format and analyze the time complexity.

“I knew it was Tower of Hanoi the second they said 'disks and pegs' so that part was fine.”

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Apple·Software Engineer·Technical Phone Screen

May 2026
Apple SWE coding round, one algorithmic question, pretty standard but the edge cases will get you if you're not careful.
  • Given an integer array, find the contiguous subarray that has the largest product and return that product.

“Tripped up on the negative number case for longer than I'd like to admit.”

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Apple·Software Engineer·Onsite - Multi Round

Jun 2026
Did a full Apple Silicon loop for a GPU IP Validation role, five back-to-back rounds on Webex covering everything from multithreading and OS internals to cache coherence and C coding. No graphics questions despite the GPU label, which surprised me. Got verbally rejected through a covering recruiter after the main one went on PTO, and both recruiters have since gone completely silent.
  • Explain how mutexes, semaphores, and condition variables work, and walk through how race conditions and deadlocks occur in multithreaded programs.
  • Walk through OS virtual memory concepts including page tables, privilege modes, and how trap handling works.
  • Design a producer-consumer protocol using a shared DRAM page, and explain how cache coherence works under the MESI protocol including memory barriers.
  • Write a function in C++ to merge two sorted linked lists.
  • Design a shared memory protocol between two processing units, covering synchronization and data consistency.
  • Given a hardware register value, write code to extract specific bits from it.
  • Declare and explain the differences between const pointers, pointers to const, and volatile pointers in C.

“This was the first real round and it set the tone.”

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Apple·Software Engineer·Hiring Manager Screen

Jun 2026
Interviewed for a business analyst role at Apple and got one question that sounds deceptively simple but really isn't.
  • What would you do if you didn't have access to the exact data you need?

“I fumbled this a bit.”

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