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Zoox interview notes, page 2 of 3

Mid-sized

Most of these Zoox write-ups come from Software Engineers (15), then Machine Learning Engineers (8) and Data Scientists (4). The most reported rounds are the technical phone screen (22), the system design round (4) and the behavioral / leadership round (1).

27 interview notes · updated Jul 2026

Zoox·Machine Learning Engineer·Technical Phone Screen

May 2026
Zoox ML engineer screen had at least one mental math / estimation question that felt more quant-interview than ML. Short round, one question I can remember.
  • You start with $1,000 and it doubles every year. Roughly how much do you have after 20 years? Walk through your mental math.

“I knew 2 to the 10th is roughly a thousand, so 2 to the 20th is about a million, then multiply by the starting $1,000 and you land near a billion.”

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Zoox·Machine Learning Engineer·Technical Phone Screen

May 2026
Zoox ML Engineer interview had at least one math/geometry problem that felt more like a puzzle than anything ML-related. Not what I was expecting.
  • In the densest hexagonal circle packing arrangement, what fraction of the plane is covered by the circles? Give a closed-form answer.

“This one threw me.”

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Zoox·Software Engineer·Technical Phone Screen

May 2026
SQL-heavy technical screen for a Data Engineer role at Zoox. One hour, two tables, three questions. The last one about data quality checks was the curveball I wasn't fully ready for.
  • Using a transactions table and a vendors table, write a SQL query to find the top 3 vendors by total amount charged over the past 2 years.
  • Extend the previous query: find the top 3 vendors by total amount charged, broken down by state and city, over the past 2 years.
  • Design a set of data quality and anomaly detection checks for this dataset, and write SQL queries to implement them.

“Pretty standard warm-up.”

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Zoox·Software Engineer·Onsite - System Design / Architecture

Jun 2026
System design round at Zoox for a software engineer role, focused entirely on designing a ride-hailing platform at Uber scale. Pretty dense session covering a lot of ground, from spatial indexing to payment consistency to surge pricing.
  • Design a large-scale ride-hailing platform like Uber, covering rider and driver matching, real-time location tracking, trip lifecycle management, fare estimation, and surge pricing.

“This is a beast of a question.”

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Zoox·Machine Learning Engineer·Technical Phone Screen

Jun 2026
Zoox ML engineer interview that was basically a coding screen dressed up as a conversation. We spent most of the time on a single stock price problem, going from brute force to optimized, which felt straightforward but had a few moments where I second-guessed myself.
  • Given an array of daily stock prices, find the maximum profit from a single buy and sell transaction where the sell must happen after the buy. Return 0 if no profitable trade exists.

“Started with the double loop and they walked me through it almost too patiently, which made me wonder if I was supposed to jump straight to the optimized version.”

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Zoox·Software Engineer·Technical Phone Screen

Jun 2026
Basic reasoning screen for a Data Engineer role at Zoox. Two questions, nothing technical in the traditional sense, more like a sanity check on whether you can think through simple problems out loud.
  • Why is summer generally hotter than winter?
  • If you invest $1,000 at a 100% annual interest rate, compounded once per year with no withdrawals, how much will you have after 20 years?

“Seemed too easy and I almost overthought it.”

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Zoox·Software Engineer·Onsite - System Design / Architecture

Jun 2026
Zoox data engineering interview, system design round focused entirely on autonomous vehicle operations. Two meaty design problems back to back, both requiring you to think about real-time pipelines and operational metrics in a domain where the stakes are pretty literal. Felt like a solid interview but the scope was enormous for a single session.
  • Design a data model to monitor the efficiency and effectiveness of a teleoperations center, including core entities, table grains, relationships, and key metrics.
  • Design a data architecture and pipeline to measure vehicle stability across an autonomous robotaxi fleet, covering data sources, ingestion, storage, transformations, quality checks, metrics, and downstream consumers.

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

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Zoox·Software Engineer·Technical Phone Screen

Jun 2026
Zoox technical screen for a software engineer role, and it was basically a full self-driving simulation problem. You're coding a lane-change decision system with kinematics, controller functions, and a time-stepping loop. More involved than I expected for a phone screen.
  • Design and implement a lane-change feature for an autonomous vehicle that decides whether a lane change is safe, modulates acceleration when it isn't, and advances the full scene forward in time using longitudinal kinematics. You're given two controller functions and must use them without substituting your own control law.

“This is a meaty one.”

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Zoox·Machine Learning Engineer·Technical Phone Screen

Jun 2026
First round at Zoox for an ML engineer role. Pretty standard stuff, CV fundamentals, background walkthrough, and a couple behavioral questions. Nothing too wild but worth knowing what to expect.
  • Walk me through your background and experience.
  • What are the fundamentals of computer vision?
  • Why are you applying for this role?
  • Why do you want to work at Zoox specifically?

“Standard opener, just went through my CV chronologically.”

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Zoox·Machine Learning Engineer·Technical Phone Screen

Jun 2026
Zoox ML engineer interview with a probability question that looks straightforward but has three parts that build on each other. The Bayesian twist in part (b) is where things get interesting.
  • You pick either a 6-sided or 8-sided die with equal probability and roll it. What is the probability of rolling a 3? Then, given you rolled a 3, what is the probability the die was the 6-sided one? Finally, using that posterior as your new prior, what is the expected value of the next roll on that same die?

“Part (a) is just total probability: (1/2)(1/6) + (1/2)(1/8) = 7/48, fine.”

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