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Lyft interview notes, page 2 of 10

Large Enterprises

Most of these Lyft write-ups come from Software Engineers (41), then Product Managers (28) and Data Scientists (19). The most reported rounds are the technical phone screen (42), the product sense round (29), the system design round (12) and the behavioral / leadership round (4).

97 interview notes · updated Sep 2026

Lyft·Software Engineer·Technical Phone Screen

Apr 2026
Lyft case question, just one estimation problem about ride volume on Halloween. Short and to the point, felt more like a screen than a full round.
  • How would you estimate the total number of Lyft rides taken on Halloween?

“I started with US population, tried to narrow down to people likely to go out on Halloween, then layered in what fraction might use Lyft vs drive or walk.”

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Lyft·Product Manager·Onsite - Product Sense / Strategy

Apr 2026
PM interview at Lyft, product sense round focused on marketplace dynamics. Just one question but it had a lot of layers to it.
  • What metrics would you track for a food delivery app, and which ones would tell you if there are too many or too few restaurants relative to order volume?

“I went straight to supply-demand ratios and talked about things like average delivery time and order fulfillment rate.”

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Lyft·Software Engineer·Onsite - System Design / Architecture

Apr 2026
Lyft system design interview, one question about building an identity platform. Pretty open-ended and I wasn't totally sure what scope they wanted.
  • Design an identity platform for Lyft.

“Spent the first few minutes just trying to nail down what 'identity' even meant in this context.”

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Lyft·Product Manager·Onsite - Product Sense / Strategy

Apr 2026
Lyft PM interview with a product strategy question on driver retention. Not a lot of context to go on, but it's the kind of question that can go sideways fast if you don't anchor on the right problem first.
  • How would you improve driver retention for Lyft?

“The scope on this is huge and I think that's the point.”

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Lyft·Software Engineer·Technical Phone Screen

Apr 2026
Lyft SWE interview with a BFS grid propagation problem. Pretty standard rotting-style question but they pushed hard on the follow-ups about multiple sources and early termination, which is where things got more interesting.
  • You're given an m×n grid where cells are either empty, secure servers, or compromised servers. Each minute, a secure server adjacent (up/down/left/right) to a compromised one also becomes compromised. Return the minimum number of minutes until all secure servers are compromised, or -1 if some can never be reached. Walk through your algorithm, explain correctness, handle multiple initial compromised sources, and discuss time and space complexity.

“Multi-source BFS, seeded with all initially compromised servers at once.”

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Lyft·Software Engineer·Technical Phone Screen

Apr 2026
Two coding problems for a Lyft software engineer round. One was a classic BFS grid problem and the other was a full key-value store with transaction support. The second one was a lot more involved than I expected going in.
  • Given an m x n grid where cells are either empty, fresh, or contaminated, find the minimum number of minutes for contamination to spread to all fresh cells via 4-directional adjacency. Return -1 if any fresh cell can never be reached.
  • Design and implement an in-memory key-value store that supports get, set, and delete operations, along with begin, commit, and rollback for nested transactions.

“Multi-source BFS, pretty standard once you recognize the pattern.”

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Lyft·Product Manager·Technical Phone Screen

May 2026
Lyft case interview, just one question about estimating revenue. Pretty stripped down, no behavioral, no follow-up rounds mentioned.
  • Estimate Lyft's total revenue.

“You have to resist the urge to just throw out a number.”

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Lyft·Product Manager·Onsite - Product Sense / Strategy

May 2026
Lyft product interview focused entirely on surge pricing, broken into three parts that escalated from problem framing to feature design to actual pricing math. Not a casual conversation.
  • What problem does surge pricing actually solve, and what metrics would tell you whether that problem exists?
  • Walk me through how you'd actually build the surge pricing feature.
  • How do you determine the actual price multiplier to apply during a surge?

“This is where I fumbled a bit.”

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Lyft·Software Engineer·Onsite - Coding / Algorithms

May 2026
Lyft coding round for a software engineer role, 90 minutes, centered entirely on building an in-memory key-value store from scratch. The interviewer pushed past the first working solution pretty quickly, which I wasn't fully expecting.
  • Implement an in-memory key-value store with put, get, and delete operations. Walk through your data structure choice and be ready to sketch an alternative approach with trade-off analysis.

“I went with a plain hashmap first, which felt obvious, and it was.”

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Lyft·Product Manager·Onsite - Product Sense / Strategy

May 2026
Lyft PM interview with a fun product design prompt about a hypothetical Apple phone with a smell-detecting sensor. The constraint was interesting: the sensor outputs text only, which forced some creative thinking about what you'd actually build around that.
  • Design an app for a new Apple phone that has a sensor capable of detecting smells. The sensor can only detect smells and output a text description of what it detects. What would you build?

“The text-only output constraint is what makes this interesting and also where I kind of stumbled.”

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