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Waymo interview notes, page 4 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·Machine Learning Engineer·Technical Phone Screen

May 2026
Waymo ML Engineer interview covering some pretty deep model optimization territory. Questions spanned QAT, knowledge distillation, contrastive learning, and evaluation, so it felt more research-adjacent than typical applied ML loops I've done before.
  • How does Quantization-Aware Training work, and what are the trade-offs compared to post-training quantization?
  • Explain how knowledge distillation works and when you would choose it over other model compression techniques.
  • How do you evaluate a machine learning model beyond standard accuracy metrics, especially in safety-critical settings?
  • What is contrastive learning and how does it differ from supervised approaches to representation learning?

“This is where I spent most of my mental energy.”

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Waymo·Machine Learning Engineer·Technical Phone Screen

May 2026
Waymo ML engineer interview that was basically a long open-ended data engineering conversation. No coding, no LeetCode, just them handing you ambiguity and watching how you swim. Felt more like a system design session than anything else, and I was not fully prepared for how much they expected me to drive it.
  • How would you approach building a pipeline to process a CSV file and prepare it for downstream engineering teams, given that you don't know the downstream requirements upfront?
  • Given a single sample row as a raw string, how would you infer a schema, assign types, and define validation rules for the data?
  • What parsing considerations would you think through for a CSV file, covering things like delimiters, quoting, escaping, and encoding?
  • How would you handle schema evolution over time, and what's your strategy for malformed or unparseable rows?
  • How would you decide on an output format and delivery mechanism for the processed data, and how would you ensure pipelines can be re-run safely?
  • How would you test this pipeline, monitor it in production, and communicate the data contract to downstream teams?

“This was the whole interview, basically.”

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Waymo·Software Engineer·Technical Phone Screen

May 2026
Waymo SWE interview with a graph/routing problem that felt pretty squarely aimed at the self-driving domain. One main coding question with a few follow-ups that escalated quickly.
  • Given a weighted undirected graph representing a map, find the shortest travel time between two nodes s and t.

“Jumped straight to Dijkstra which was the right call, and remembered to add early termination once t gets dequeued.”

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Waymo·Software Engineer·Technical Phone Screen

May 2026
Waymo coding interview with a single algorithmic question about big number arithmetic. Not much context on how it went but the problem itself is a classic string manipulation trap that's easy to underestimate.
  • Given two strings where each represents a number too large to fit in a 32-bit integer, how would you add them together and return the result as a string?

“Looks simple until you realize you can't just convert to int and call it a day.”

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

May 2026
Waymo ML engineer interview with a system design question around video retrieval for autonomous driving scenarios. Pretty focused and technical, no fluff.
  • You're given a video clip of a driving scene (like a near-collision or heavy rain). Design a system that retrieves similar scenes from a massive video dataset.

“This is the kind of question where you can go a hundred directions and that's exactly what tripped me up at first.”

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Waymo·Software Engineer·Technical Phone Screen

May 2026
Waymo SWE interview with a knight moves problem on a partially blocked chessboard. Pretty clean algorithmic round, nothing too wild, though the edge cases are where things get interesting.
  • Given an N x N chessboard with some blocked cells, a knight's start position, and a target position, find the minimum number of moves for the knight to reach the target. Return -1 if it's unreachable. The knight can jump over blocked cells but cannot land on them.

“BFS was the obvious move here (pun intended).”

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Waymo·Mobile Engineer·Technical Phone Screen

May 2026
Did a first round for a Mobile Engineer role at Waymo. They had me open Android Studio live and build a pickup screen using Jetpack Compose. Answered everything they asked but still didn't move forward, which was frustrating.
  • Build a Waymo ride pickup screen in Jetpack Compose, incorporating a list view, live data updates, and currency conversion.

“Pretty involved for a first round.”

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Waymo·Software Engineer·Onsite - System Design / Architecture

May 2026
Waymo system design round, one big open-ended question that basically asked me to design a whole evaluation-as-a-service platform from scratch. Dense problem with a lot of moving parts and I'm not sure I covered everything they wanted.
  • Design an evaluation platform that supports both human reviewers and LLM-based judges, covering task ingestion and routing, evaluator pool management, quality control mechanisms, consensus aggregation, throughput and SLA guarantees, cost trade-offs, and customer-facing APIs.

“This question is basically six questions stapled together.”

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

May 2026
Waymo ML Engineer interview that went deep into accelerator runtime optimization. The question was basically one big open-ended design problem and they let it run for a while, which I wasn't fully prepared for.
  • You're working on an ML framework runtime running on a custom accelerator. A model is showing high latency and occasional memory pressure. Walk through how you'd profile and optimize it, covering tensor kernels, memory layout, operator scheduling, and kernel fusion. Also discuss the tradeoffs between throughput, latency, memory usage, numerical correctness, and maintainability.

“This question is basically its own interview.”

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Waymo·Software Engineer·Technical Phone Screen

May 2026
Waymo SWE interview with a tricky in-place matrix copy problem. The overlap handling is where things get interesting and where I definitely stumbled a bit before finding my footing.
  • Given a 2D matrix and two rectangular regions (each defined by a top-left corner, height, and width), copy the source rectangle into the destination rectangle in place using O(1) extra memory. The rectangles may overlap. How do you handle the iteration order to avoid corrupting source data before it's read, and what do you do about out-of-bounds destinations?

“My first instinct was just to loop top-to-bottom, left-to-right and copy each cell.”

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