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Applied Intuition interview notes, page 3 of 7

Mid-sized

Most of these Applied Intuition write-ups come from Software Engineers (50), then Machine Learning Engineers (12) and Mobile Engineers (2). The most reported rounds are the technical phone screen (42), the system design round (14), the hiring manager screen (4) and the recruiter screen (2).

64 interview notes · updated Jul 2026

Applied Intuition·Software Engineer·Technical Phone Screen

May 2026
Interviewed for a software engineering role at Applied Intuition and got a computational geometry problem that felt way more niche than the typical leetcode grind. The core challenge was merging overlapping line segments in a plane, which sounds straightforward until you actually sit down and think through all the edge cases.
  • Given a list of planar line segments defined by their endpoints, merge any segments that overlap. Two segments overlap if they are collinear and their projections onto the shared line intersect or touch. Return the minimal set of merged segments.

“I knew the 1D interval merge part cold (basically the classic merge intervals problem), but grouping segments by their actual line identity tripped me up.”

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Applied Intuition·Software Engineer·Technical Phone Screen

May 2026
Interviewed for a software engineer role at Applied Intuition and got a classic LRU-style problem dressed up as a task scheduler. Pretty standard for this type of company but the variants they mentioned kept it from being totally autopilot.
  • Design and implement a task scheduler that manages a fixed-capacity pool of tasks, supporting scheduling new tasks and accessing existing ones, with least-recently-used eviction when the pool is full.

“Basically LC 146 with a costume on.”

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Applied Intuition·Software Engineer·Onsite - System Design / Architecture

May 2026
Applied Intuition system design round for a software engineer role. The whole thing was focused on building a task scheduler from scratch, which sounds straightforward until you actually have to talk through edge cases for 45 minutes.
  • Design a single-CPU, single-thread task scheduler with APIs for one-time tasks at an absolute time, one-time tasks after a delay, and periodic tasks that repeat on a fixed interval. Walk through the data structure, the core loop, and how you handle late wake-ups, clock drift, and cancellation.

“I went straight to a min-heap sorted by next-fire time, which felt right and they didn't push back on it.”

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Applied Intuition·Software Engineer·Technical Phone Screen

May 2026
Applied Intuition coding round focused entirely on a coupon engine design problem, split into two parts that escalated pretty fast from basic cart math to a full class design with complexity analysis and unit tests.
  • Design and implement a coupon application engine for a shopping cart. A coupon has applicable categories, minimum item count and price requirements, a percentage discount, and a flat value discount. Given one coupon and a list of cart items, compute the final price after applying the coupon once. How do you handle rounding, and in what order do you apply the percentage vs. flat discount?
  • Extend the coupon engine to support coupons that apply across multiple categories in the same cart. Walk through your data structures and class interfaces, explain the time and space complexity, and provide unit tests covering edge cases like no eligible items, overlapping categories, and zero or negative totals.

“I started coding before thinking through the rounding question and that came back to bite me.”

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Applied Intuition·Software Engineer·Technical Phone Screen

May 2026
Got a coding problem at Applied for a software engineer role, basically a filesystem duplicate finder. The problem itself was clean but the follow-ups pushed into system design territory pretty fast.
  • Given a list of files each with a full path and size, find all groups of duplicate files based on identical content. Groups of size one should be excluded from the output.
  • How would you design this to avoid hashing every file when most files are unique?
  • How do you handle extremely large files, say over a gigabyte, without loading the whole thing into memory?
  • If hash collisions are a concern, how would you confirm two files are actually duplicates?

“The core problem is straightforward enough but the real trick is not hashing everything blindly.”

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Applied Intuition·Machine Learning Engineer·Onsite - System Design / Architecture

May 2026
Applied Intuition ML engineer interview, system design round focused entirely on KV caching for transformer inference. Pretty deep technically, they wanted actual tensor shapes and API signatures, not just hand-waving about attention.
  • Design and implement a key-value caching system for autoregressive inference in a Transformer decoder. Include tensor shapes, a per-layer cache API that works across decoding steps and batched inputs, memory limit handling, and support for both greedy and beam search.
  • Walk through the complexity analysis and expected speedup of KV caching compared to full recomputation at each decoding step.
  • How would you test correctness of the KV cache implementation, particularly for edge cases like an end-of-sequence token appearing in the middle of a batch?

“This one took me a minute to scope properly.”

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Applied Intuition·Software Engineer·Technical Phone Screen

May 2026
Interviewed for a software engineer role at Applied Intuition and got a coding problem around mesh/vertex compression. Pretty niche stuff compared to the usual leetcode grind, which I appreciated even if it threw me off a bit.
  • Given a list of fixed-size vertex arrays (like 3D coordinates), some of which are duplicates, implement a compression function that returns the deduplicated vertices in first-occurrence order and an index array mapping each original vertex to its position in the deduplicated list.

“My first instinct was to just reach for a hashmap keyed on the array contents, which worked fine conceptually, but I fumbled around for a bit figuring out how to hash a small fixed-length array cleanly.”

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Applied Intuition·Software Engineer·Technical Phone Screen

May 2026
Got a geometry problem at Applied for a software engineer role. One question, pretty involved, the kind where you think you have it figured out and then realize the transitive merging part is way harder than it looks.
  • Given a list of 2D line segments where each segment is represented as an unordered set of collinear points (including possible interior points), merge all segments that lie on the same infinite line and whose projections overlap or touch. Transitive merges count. For each merged result, return all unique points from the contributing segments, ordered along the line.

“The collinearity check and line parameterization tripped me up more than I expected.”

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Applied Intuition·Software Engineer·Technical Phone Screen

May 2026
Interviewed for a software engineer role at Applied Intuition and got a coding question that was basically a LeetCode problem dressed up with a real-world spin. The follow-up about optimization is where things got interesting.
  • Given a file directory tree, implement an algorithm using DFS or backtracking to find and delete files with duplicate content. Then discuss how you would optimize it to run faster.

“The base problem is pretty recognizable if you've done file system stuff before.”

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Applied Intuition·Mobile Engineer·Technical Phone Screen

May 2026
Applied Intuition mobile engineer interview with a coding problem around button press classification. Pretty embedded/systems-flavored for a mobile role, which I wasn't expecting.
  • Design a button click detector that reads a stream of samples (1=pressed, 0=released, sampled every 10ms) and classifies each press as a single click (under 200ms) or long click (over 500ms), handling multiple buttons concurrently and consecutive presses.

“The ambiguous zone between 200ms and 500ms is what got me.”

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