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Airbnb interview notes, page 15 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·Product Manager·Onsite - Product Sense / Strategy

Jun 2026
Interviewed at Airbnb for a product role and got hit with a pretty open-ended strategy question about building something from zero. Not a lot of context to work with, which made it harder than it sounds.
  • How would you define and execute a product strategy for launching something entirely from scratch?

“I fumbled the opening because I tried to jump straight into frameworks instead of anchoring on the problem first.”

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Airbnb·Software Engineer·Onsite - Behavioral / Leadership

Jun 2026
Interviewed for an EM role at Airbnb and got hit with the management style question pretty early. Short post, just the one question worth flagging.
  • How would you describe your management style, and can you give some concrete examples of it in practice?

“I rambled a bit trying to cover too many angles at once.”

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Airbnb·Software Engineer·Onsite - System Design / Architecture

Jun 2026
Airbnb system design round focused entirely on scaling a host listings dashboard. The problem was well-scoped but had a lot of moving parts, and I felt like I was playing catch-up the whole time.
  • Design the backend for a host listings page that shows aggregated metrics (nights booked, average price) across a date range the host selects, and make it fast when a host has 100+ listings.
  • How do you handle edge cases like partial date overlaps and cancelled reservations when computing nights booked?
  • How would you keep the aggregated metrics up to date as new reservations come in or existing ones change?
  • What are your performance goals for this page and how would you validate that the design actually meets them?

“This is basically a read-heavy aggregation problem with a date filter on top, and I spent too long talking about the API shape before getting to the actual bottleneck.”

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

Jun 2026
ML system design interview at Airbnb for an MLE role, basically one long deep-dive into building a search ranking system from scratch. Pretty thorough coverage of the whole stack, from retrieval pipelines to fairness concerns to A/B testing.
  • How would you frame the search ranking problem for Airbnb? Should you use pointwise, pairwise, or listwise learning-to-rank, and what label would you use (booking, click, or something else)?
  • Walk me through the data sources you'd use to train the ranking model. What features come from listings, hosts, users, and the query context itself?
  • Describe the two-stage retrieval and ranking pipeline you'd build. How does the candidate retrieval stage differ from the final ranker?
  • What features would you engineer for the ranker? Think about listing quality, price competitiveness, host responsiveness, and personalization.
  • What model architecture would you choose for the ranker, and why? Compare gradient boosted trees versus a neural ranker.
  • What offline and online metrics would you use to evaluate the ranking system?
  • How would you handle cold-start for new listings and new users who have no historical data?
  • How do you ensure fairness and result dispersion in the ranked list? What happens if the model always surfaces the same top listings?
  • How would you handle online serving given latency constraints, and how would you design an A/B test to validate the new ranker?

“This is where I spent probably too long.”

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Airbnb·Software Engineer·Onsite - System Design / Architecture

Jun 2026
System design round at Airbnb for a software engineer role, focused entirely on designing a booking system end to end. Pretty intense scope for a single session.
  • Design a booking system (like for hotels or flights). Walk through functional requirements, data model, concurrency handling, and overall architecture.
  • How do you prevent double-booking under high concurrency? What are the tradeoffs between your options?
  • How would you design the payment workflow to be idempotent and handle failures gracefully?
  • How would you keep search results low-latency while maintaining strong consistency on inventory?

“This was the whole interview.”

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Airbnb·Software Engineer·Onsite - Coding / Algorithms

Jun 2026
Airbnb coding round for a software engineer role. One problem, 45 minutes, and somehow they expect you to write code, build test cases from scratch, and handle a follow-up that's genuinely harder than the original. I came in strong on linked lists and still didn't finish.
  • Given two linked lists, each of which may or may not contain a cycle, determine whether they share at least one node.
  • Follow-up: modify your solution to return the actual intersecting node, not just whether one exists.

“My linked list fundamentals are solid so I got through the main logic fairly fast.”

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Airbnb·Machine Learning Engineer·Onsite - Coding / Algorithms

Jun 2026
Airbnb MLE coding round with a coin change problem that had a float twist. The float precision pitfall is the kind of thing that seems obvious in hindsight but absolutely isn't in the moment.
  • Given a list of coin denominations expressed as floats (e.g. 0.25, 0.5, 1.0), determine whether a target value can be made from those coins, or find the minimum number of coins needed.

“Started doing DP straight on the float values and got maybe halfway through before the interviewer nudged me about precision.”

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Airbnb·Software Engineer·Onsite - Coding / Algorithms

Jun 2026
Airbnb coding round that went sideways fast. The question itself was reasonable but the interviewer showed up underprepared, with a broken JavaScript test class she hadn't vetted, and the whole session devolved into live debugging her own code rather than evaluating mine.
  • Implement a merged iterator over multiple streams (byte or char iterators) that reads one element from each stream in round-robin order, skipping exhausted streams. Must support has_next() and next().

“The question itself is fine, pretty standard iterator design.”

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Airbnb·Software Engineer·Technical Phone Screen

Jun 2026
Airbnb SWE interview with a combinatorics/optimization problem that felt deceptively simple at first glance. The small constraint on distinct food types was the key unlock, and I almost missed it.
  • You're given a list of menu items where each item is a (set of foods, price) pair. Given a list of wanted foods, find the minimum total cost to acquire at least all the wanted foods by purchasing some combination of items. Return both the cost and the actual items chosen.

“I spent the first few minutes trying to think of this as a greedy problem, which was a mistake.”

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Airbnb·Software Engineer·Onsite - Coding / Algorithms

Jun 2026
Airbnb coding round with a pretty gnarly interval/availability problem that took me a while to fully parse. The problem was dressed up in product language but the core was algorithmic, which I should've seen faster.
  • Given a set of listings each with availability as a sorted list of day integers, and a requested date range [S, E], find all unordered pairs of listings that can form a valid split stay covering the full range. A valid split requires some cutoff T where one listing covers S through T consecutively and another covers T+1 through E consecutively. Discuss algorithm, complexity (aim for better than O(L² · R)), and edge cases like missing boundary days or overlapping coverage.

“The product framing tripped me up longer than I'd like to admit.”

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