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Waymo interview notes, page 5 of 9

Large Enterprises

Most of these Waymo write-ups come from Software Engineers (46), then Machine Learning Engineers (23) and Data Scientists (10). The most reported rounds are the technical phone screen (58), the system design round (11), the behavioral / leadership round (6) and the hiring manager screen (4).

87 interview notes · updated Jul 2026

Waymo·Software Engineer·Technical Phone Screen

May 2026
Waymo SWE interview with a shortest path graph problem. Pretty standard stuff if you've done any LeetCode graph prep, but still worth knowing cold.
  • Given a start node, a set of target nodes, and weighted edges between nodes, find the shortest path from the start to each target.

“Classic Dijkstra setup.”

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Waymo·Software Engineer·Technical Phone Screen

May 2026
Waymo SRE interview with a coding problem that's deceptively algorithmic for the role. The question felt more like a software engineering screen than anything ops-flavored, which threw me a bit.
  • You have a number line from 0 to 50. Points arrive one at a time as floating-point values, and each point contaminates the interval one half unit on either side. Intervals can overlap and contamination is permanent. Design a function add(p) that returns true if and only if the full range [0, 50] is covered after adding that point.

“I went with a sorted list of merged intervals and a running total of covered length.”

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Waymo·Machine Learning Engineer·Technical Phone Screen

May 2026
Waymo ML engineer interview with a problem I didn't fully expect: given raw 3D trajectory data, figure out how to preprocess and tokenize it so a model can actually predict the next step in the sequence. More engineering judgment than pure ML theory.
  • You're given 3D trajectory data. How would you preprocess and tokenize it into a format suitable for predicting the next step in the sequence?

“This one took me a second to even figure out where to start.”

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Waymo·Machine Learning Engineer·Technical Phone Screen

May 2026
Waymo ML Engineer interview with a coding round focused on data structures. The problem was a trie implementation for prefix search, which sounds straightforward until you're also expected to walk through complexity tradeoffs on the spot.
  • Given a list of words, design a data structure that takes a prefix string and returns all words in the list that start with that prefix. Walk through your implementation and analyze the time complexity.

“I went with a trie, which felt like the obvious move.”

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Waymo·Machine Learning Engineer·Technical Phone Screen

May 2026
Waymo ML engineer interview with a physics/spatial reasoning problem involving two colliding objects and a diagram. Pretty niche question, not your typical ML theory stuff.
  • Given two objects on a collision course, use the provided diagram to determine what the outcome of the collision will be.

“This one threw me a bit.”

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Waymo·Software Engineer·Technical Phone Screen

May 2026
Waymo software engineer screen, coding focused. The Fibonacci generator question sounds deceptively easy but they pushed pretty hard on the memory and interface tradeoffs, which is where things got interesting.
  • Implement a generator that lazily and indefinitely yields Fibonacci numbers. Walk through memory usage and explain how this differs from returning a precomputed list. Optionally add support for a count or upper bound parameter.

“I got the basic generator working fine, two variables, yield, loop forever.”

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Waymo·Software Engineer·Onsite - Behavioral / Leadership

Jun 2026
Interviewed at Waymo, looks like a leadership-focused round. Just the one question from what I can tell, centered on team building and internal brand.
  • How have you helped your team reach new goals and establish a strong reputation within the broader organization?

“I went with a story about a team that was kind of invisible before I joined, no one really knew what we did.”

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Waymo·Machine Learning Engineer·Onsite - Coding / Algorithms

Jun 2026
Waymo ML engineer interview with a debugging-heavy coding round. They handed me a small tensor utility library with three distinct bugs and asked me to find them, fix them, and write tests. Not the typical leetcode grind, which I appreciated, but the aliasing bug in particular took me longer than I'd like to admit.
  • Given a buggy tensor utility library with issues in matrix initialization, array conversion, and chunk splitting, identify all the bugs, fix them, and add tests covering aliasing, shape correctness, and non-divisible chunk sizes.

“The aliasing one is sneaky.”

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Waymo·Data Scientist·Technical Phone Screen

Jun 2026
Waymo data scientist interview with a meaty product analytics case built around a ride-hailing feature called Smart Wait. The whole thing was basically one extended scenario with four parts, and the difficulty ramped up fast once you got past the surface-level agreement or disagreement question.
  • A PM says fleet efficiency improved because actual time to pickup decreased after the Smart Wait feature launched. Do you agree with that conclusion?
  • What alternative explanations could account for the decrease in time to pickup, particularly given that conversion dropped at the same time?
  • What metrics and analyses would you use to determine whether Smart Wait was actually a net positive for the product?
  • If you were running an experiment on this feature, what would you randomize, what would be your primary metric, and what guardrail metrics would you track?

“I said yes too quickly and then had to walk it back.”

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Waymo·Machine Learning Engineer·Technical Phone Screen

Jun 2026
Waymo ML Engineer interview, got a maze robot problem that looked like a graph question but turned out to be something weirder. Took me a while to even understand what was being asked.
  • Given a 2D maze grid where cells are walls, empty spaces, or a single exit, design an instruction sequence (using U/D/L/R moves) such that a robot with no knowledge of its starting position is guaranteed to reach the exit after executing the full sequence. The robot stays put if a move would hit a wall or go out of bounds.

“Spent the first few minutes just re-reading the problem because I kept thinking it was a shortest-path thing.”

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