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Waymo interview notes, page 6 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

Jun 2026
Waymo SWE interview with a math-heavy coding problem that looks straightforward until you remember parabolas aren't monotonic. The two-pointer insight is the whole key and if you don't see it fast you're basically stuck.
  • Given a sorted integer array and three coefficients a, b, c, apply the quadratic function f(x) = a*x^2 + b*x + c to every element and return the results in sorted order.

“My first instinct was to just map and sort, which is O(n log n) and they clearly wanted better.”

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Waymo·Software Engineer·Onsite - Coding / Algorithms

Jun 2026
Coding round at Waymo for a software engineer role. One meaty graph traversal problem with follow-ups, and they wanted runnable code with a main method, not pseudocode.
  • Given an N x N chessboard, a starting cell, and a target cell, find the minimum number of moves for a chess knight to travel from start to target. The board is bounded, so the knight cannot leave the grid. Return -1 if the target is unreachable.

“BFS was the right call and I knew it, but I still spent a couple minutes talking through DFS before landing there.”

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Waymo·Machine Learning Engineer·Technical Phone Screen

Jun 2026
Waymo ML Engineer interview had me coding a neural network from scratch in NumPy, no frameworks allowed. Pretty brutal if your backprop math is rusty, but also kind of a fun problem once you get into it.
  • Implement a two-layer feed-forward neural network from scratch using only NumPy, including forward pass, backward pass with chain-rule gradients, and SGD parameter updates. Train it on a toy dataset and show the loss going down.
  • Walk through weight initialization strategies: why does initializing all weights to zero fail, and how does Xavier initialization help?
  • Why does ReLU help with the vanishing gradient problem compared to sigmoid or tanh?
  • How would you verify your manually coded gradients are correct using finite differences?

“This was the whole interview basically.”

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Waymo·Machine Learning Engineer·Technical Phone Screen

Jun 2026
Waymo ML engineer interview had a heavy emphasis on implementing algorithms from scratch, no libraries allowed. You really need to know the math cold, not just the API calls.
  • Implement linear regression from scratch using gradient descent. Walk through the cost function, derive the gradient update, and compare the iterative approach to the closed-form solution.
  • Build a K-nearest neighbors classifier from scratch. What data structures would you use, how do you implement fit and predict, and what's the time complexity?
  • Explain how you'd implement a decision tree split using information gain. How does the algorithm decide which feature to split on?
  • Implement a Naive Bayes classifier from scratch. Cover the data structures, the fit and predict methods, and how you'd handle zero probabilities.

“This is where I spent most of my prep and it still felt shaky in the moment.”

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Waymo·Software Engineer·Technical Phone Screen

Jun 2026
Waymo SWE interview, coding round, one graph problem the whole session. Screen sharing was mandatory the entire time which added a weird layer of pressure I wasn't fully prepared for.
  • Given a list of (parent, child) edge pairs representing a graph, determine whether the graph forms a valid forest (i.e., one or more valid trees with no cycles and no disconnected anomalies). You also need to design your own test cases.

“The test case design part tripped me up more than the actual algorithm.”

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Waymo·Software Engineer·Technical Phone Screen

Jun 2026
Waymo SWE interview with a geometry/string manipulation problem that looks deceptively simple but has a few gotchas once you start coding it up. One round, coding focused.
  • You're given an array of digits representing a 7-segment LED display. After rotating the entire display 180 degrees, does it show the same number? Return true or false.

“I got the basic idea fast enough: only certain digits survive rotation (0, 1, 2, 5, 6, 8, 9) and the sequence reverses.”

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Waymo·Data Scientist·Technical Phone Screen

Jun 2026
Waymo data scientist interview with a pretty gnarly statistics/sampling problem. One question, but it had enough layers to keep me busy for a while. Not your typical SQL or A/B test setup.
  • You run a restaurant with 10,000 reservations in a day. Each reservation has a reserved party size and an actual show-up count. You only observe 1,000 of these reservations, but the sampling is size-biased: larger reservations are proportionally more likely to be sampled. How would you estimate the total number of people who actually show up across all 10,000 reservations, and how would you quantify uncertainty around that estimate?

“The size-biased sampling part is what trips you up if you're not careful.”

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Waymo·Software Engineer·Onsite - Coding / Algorithms

Jun 2026
Waymo SWE interview threw a real curveball: implement a self-balancing BST completely from scratch, no standard library crutches. The kind of question that sounds doable until you're actually staring at rotation logic under pressure.
  • Without using any built-in data structures from the standard library, implement a self-balancing binary search tree (AVL or red-black) from scratch, including your own node definition, rotations, rebalancing, and support for insert, delete, and lookup all in O(log n).

“I went with AVL because I felt shakier on red-black coloring rules under pressure.”

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Waymo·Software Engineer·Technical Phone Screen

Jun 2026
Waymo software engineering interview that threw a pretty nasty low-level data structures problem at me. The whole thing was about reimplementing frozenset from scratch, no standard library shortcuts allowed.
  • Without using any built-in hash-based data structures, implement a frozenset from scratch in Python. It needs to support membership testing, length, iteration, equality comparison, and produce a stable hash. You have to build the underlying hash table yourself using only arrays.

“This wrecked me a little.”

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Waymo·Product Manager·Onsite - Product Sense / Strategy

Jun 2026
Waymo PM interview with a product strategy question about autonomous vehicle simulation. Pretty technical context for a PM role, which I wasn't fully expecting.
  • Engineers are saying the simulation used to train autonomous vehicles isn't realistic enough. As a PM, how do you handle this?

“I went straight into stakeholder alignment and roadmap prioritization mode, which felt right but I think I missed something.”

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