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Airbnb interview notes, page 16 of 19

Large Enterprises

Most of these Airbnb write-ups come from Software Engineers (141), then Machine Learning Engineers (19) and Data Scientists (12). The most reported rounds are the technical phone screen (85), the system design round (47), the behavioral / leadership round (20) and the product sense round (13).

187 interview notes · updated Oct 2026

Airbnb·Software Engineer·Technical Phone Screen

Jun 2026
Airbnb software engineering interview that was essentially a deep code review exercise on a geospatial processing module. Covered a lot of ground: bugs, performance, testing, security, the works. More breadth than I expected for a single session.
  • You're handed a Python module that reads geospatial data (CSV and GeoJSON), computes distances between points, clusters nearby locations, and writes summaries. Walk through a code review: what correctness bugs, numerical issues, and edge cases would you flag?
  • What performance improvements would you propose for this geospatial pipeline, specifically around vectorization, spatial indexing, and I/O batching?
  • How would you refactor this module to improve maintainability? Think about modularization, type hints, and documentation.
  • What security considerations apply to a module like this, particularly around input validation and dependency management?
  • Outline a testing strategy for this module, including unit and integration tests. What fixture data would you use?
  • Estimate the time and space complexity of the critical paths in this pipeline, particularly distance computation and clustering.
  • Which Python libraries would you choose for this geospatial pipeline (e.g. pandas, shapely, pyproj) and what are the trade-offs between them?

“The CRS mismatch thing is what I led with, which felt right in hindsight.”

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Airbnb·Software Engineer·Onsite - System Design / Architecture

Jun 2026
Airbnb system design round focused on building a query system for user search and order history with time-range and geo filters. Pretty meaty problem that touched on ingestion, storage tradeoffs, and caching all in one go.
  • Design a system that lets users query their own search and order history, with filtering by time range and geographic location, sorted by time.

“This one sprawled fast.”

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Airbnb·Backend Engineer·Onsite - System Design / Architecture

Jun 2026
System design round at Airbnb for a backend role, focused entirely on designing the search and booking infrastructure at scale. Pretty intense scope, they wanted ML integration and geo-sharding discussed on top of the core architecture, which I wasn't fully expecting.
  • Design the backend system powering Airbnb's home page, listing search, and availability/booking flow at scale.
  • How would you handle cache invalidation when listing availability changes frequently?
  • Walk through how you'd integrate ML-based personalized ranking into the search results pipeline.
  • What consistency model would you use for the availability and booking inventory service, and why?
  • How would you structure A/B testing for ranking changes without polluting the experiment with network effects between users?

“This is basically three problems jammed into one.”

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Airbnb·Software Engineer·Onsite - System Design / Architecture

Jun 2026
Airbnb system design round for a software engineer role, heavy ML focus. The whole session was basically one giant open-ended question about building a customer LTV system from scratch, which sounds manageable until you realize how many moving parts they actually want you to cover.
  • Design a complete machine learning system to estimate customer lifetime value on a platform. Cover everything from defining what LTV means for the business, to data pipelines, modeling choices, offline and online architecture, how scores get used downstream, and how you'd run experiments to validate impact.

“This is a beast of a question and I did not pace myself well.”

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Airbnb·Software Engineer·Technical Phone Screen

Jun 2026
Airbnb software engineer interview focused almost entirely on a single meaty optimization problem involving combo pricing and dynamic programming. The follow-ups kept coming and I was not fully prepared for how deep they wanted to go on complexity analysis and the N=3 special case.
  • Given N menu items each with a unit price and a list of combo offers (each specifying quantities of certain items and a bundled price), write an algorithm that finds the minimum cost to fulfill a specific order without purchasing any extra items. Walk through your state definition, transitions, and base cases for a DP or memoized approach, and analyze time and space complexity in terms of N, Q (max quantity needed per item), and S (number of offers).
  • When N is fixed at 3, how would you redesign the solution using an explicit 3D state (i, j, k) to reduce overhead? What preprocessing steps like pruning dominated offers or capping offer quantities to actual needs would you apply, and what does the resulting complexity look like?
  • What additional practical optimizations can you apply, such as skipping offers that exceed current needs mid-search or reordering state dimensions to allow bottom-up computation instead of top-down memoization?

“This took me a while to frame correctly.”

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Airbnb·Software Engineer·Technical Phone Screen

Jun 2026
Airbnb software engineer interview with a coding question around text formatting. The problem had enough edge cases to keep you busy, and the greedy approach felt obvious in hindsight but took a minute to land on during the actual session.
  • Write a function that takes a list of articles (each article being a string or list of words) and a max line width, then formats them into lines. Rules: no line exceeds the width, words can't be split, no line starts with punctuation, avoid leaving a single word alone on a line when possible, and insert a '----' separator between consecutive articles. Return the full list of lines.

“The punctuation-leading rule is what bit me first.”

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Airbnb·Software Engineer·Onsite - System Design / Architecture

Jun 2026
Airbnb system design round for a software engineer role. The question was a Connect Four style OOP design problem and it went deeper than I expected, covering extensibility and testing strategy on top of the core class design.
  • Design an object-oriented model for a turn-based, grid-based drop token board game similar to Connect Four, including class responsibilities, extensibility for different win conditions or board configurations, and a testing approach for win-checking and move validation.

“I started with the obvious classes, Game, Board, Player, Move, and then they pushed me on how I'd make win conditions swappable.”

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Airbnb·Software Engineer·Technical Phone Screen

Jun 2026
Airbnb SWE interview that went deep into a restaurant menu optimization problem. Three sub-questions, each harder than the last. The combo pruning part at the end was where I really started to lose the thread.
  • You have a restaurant menu with single items (each with a price) and combo offers (each specifying quantities of items and a total price). Given a customer order specifying exact quantities needed for each item, find the minimum cost to fulfill the order exactly. You can buy individual items or combos, but cannot purchase more of any item than what's needed. Describe an algorithm, justify its correctness, and analyze time and space complexity.
  • If the order only involves three distinct item types (all other items have zero need), how would you optimize the solution? Describe the state representation, transition design, and the resulting complexity improvement.
  • What preprocessing or pruning would you apply to eliminate dominated or irrelevant combos and items before running the main algorithm, and how would you prove that removing them doesn't change the optimal answer?

“My first instinct was BFS on a state space where each state is the remaining need vector, then I pivoted to DP with memoization.”

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Airbnb·Software Engineer·Technical Phone Screen

Jul 2026
Airbnb coding round, linked list problem that sounds manageable until you realize there are three separate cases to handle. Took me a bit to work through the cyclic-plus-cyclic scenario without fumbling.
  • Given two singly linked lists that may each independently contain a cycle, determine whether the two lists share any node in common.

“I got the acyclic case pretty fast, tail comparison or the length-difference two-pointer thing.”

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Airbnb·Software Engineer·Technical Phone Screen

Jul 2026
First round technical screen for an iOS Engineer role at Airbnb. Pretty straightforward, one math-based UI layout problem with a follow-up that added a layer of complexity. Passed and got the notification about a week later.
  • Given a UI view layout problem, write the code to implement the layout. Then, if that view is nested inside a relative container, how would you modify your solution?

“The base question was fine, I had something working pretty quickly.”

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