Learn how to prepare for Waymo interviews and how to get a job at Waymo with this in-depth guide.

We break down the Waymo interview process and the top questions you should expect to answer.

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Verified: This guide was created with insights from a recent Waymo hire who completed the full ML engineering interview loop.

About Waymo

What is Waymo?

Waymo is an autonomous driving technology company and a subsidiary of Alphabet (Google's parent company). Originally launched as Google's self-driving car project in 2009, Waymo became a standalone company in 2016. It operates Waymo One, a commercial robotaxi service running in Phoenix, San Francisco, Los Angeles, and Austin, making it the most widely deployed autonomous ride-hailing service in the world.

Where is Waymo located?

Waymo is headquartered in Mountain View, California, with engineering offices across the Bay Area. The company also has operations in Phoenix, Los Angeles, Austin, and a growing international presence including London. Waymo employs over 2,500 people. You can browse open roles on the Waymo careers page.

Who does Waymo hire?

Waymo hires software engineers, machine learning engineers, robotics engineers, product managers, and operations specialists. For ML roles, the bar is notably high.

Waymo expects candidates to demonstrate both strong software engineering skills and deep ML knowledge. A software engineer might pass the initial coding screen but struggle on ML system design, while a pure ML researcher might fail the LeetCode-style coding round. The ideal candidate combines both. You can learn more about the culture and teams at Waymo.

Waymo Interview Resources

Waymo Interview Process

The Waymo hiring process follows a Google-style structure:

Recruiter phone screen: A brief introductory call covering your background and interest
Technical coding screen: A medium-to-hard data structures and algorithms problem
Recruiter prep call: A scheduling call before the final loop where you can ask questions about each round
Final interview loop: Five to six rounds covering coding, ML coding, ML system design, and two behavioral interviews

The Waymo hiring process is structured and thorough, reflecting its Alphabet heritage. The coding bar is equivalent to a software engineering interview, which catches many ML candidates off guard.

How long does the interview process take?

Expect 4 to 6 weeks from application to offer. After passing the initial tech screen, you'll have a prep call with your recruiter before the final loop. The final loop can be spread across multiple days for scheduling flexibility.

Does Waymo's interview process vary by role?

Yes. Machine learning engineers face a particularly demanding loop that includes both traditional coding rounds and ML-specific rounds. The process is identical for senior and staff candidates.

Leveling happens post-loop based on performance. Staff-level candidates need to demonstrate they've driven high-impact projects; if you fall short on the behavioral assessment but pass technically, you can still receive a senior offer.

Is there a take-home assignment?

No. All evaluation happens through live interviews.

How does Waymo make hiring decisions?

Waymo uses the same loop for senior and staff candidates and determines leveling afterward. Technical performance sets the bar for both levels.

The differentiator for staff is behavioral: you need to demonstrate leadership on high-impact, long-duration projects involving cross-team coordination. If you meet the technical bar but not the leadership bar, you'll be offered a senior role instead.

Recruiter Screen

What is the Waymo recruiter screen?

A brief introductory call covering your background, current work, and interest in Waymo. This is logistical rather than evaluative. Clearly communicate what you're working on now and what you've done in the past. The recruiter will also ask about your experience level as an ML project leader, particularly projects with high complexity.

How should I prepare for the recruiter call?

Have a concise answer for why Waymo specifically. Research the team you're applying to. Waymo's teams include Perception, Prediction, Planning, Simulation, and Infrastructure. Know which domain interests you and why your background fits.

Technical Coding Screen

What is Waymo's technical screen?

A coding interview using a traditional data structures and algorithms format. Expect a medium-to-hard difficulty problem.

One candidate received a BFS-based problem involving simulating an organizational hierarchy: model it as a tree, then answer queries like "find all direct reports" and "find everyone in a department."

When Waymo says "coding round," clarify whether it's a pure LeetCode-style problem or an ML coding problem. Recruiters sometimes use "coding round" to describe both, which can catch candidates off guard during prep.

Ask explicitly: "Is this a LeetCode-style DSA problem, or will it involve ML coding? Will I need numpy, PyTorch, or basic Python?" The recruiter may not volunteer this distinction, and it changes your prep significantly.

Is the technical screen difficult?

Yes, more than candidates typically expect for an ML role. The DSA bar at Waymo is equivalent to a software engineering interview: medium to hard LeetCode difficulty.

This is the round where many strong ML engineers stumble because they've underprepared for algorithmic problems. Practice with our mock interview tools to build speed.

Final Interview Loop

What is Waymo's final interview loop?

The final loop consists of five to six interviews that can be spread across multiple days. For ML engineering roles, expect:

One additional coding round (DSA, similar to the screen but more practical and potentially domain-relevant)
One ML coding round (numpy data manipulation, building ML components)
One ML system design round (discussion-based, not whiteboard-heavy)
Two behavioral rounds (one leadership-focused project deep dive, one traditional behavioral)

Each session runs about 45 to 60 minutes.

What types of rounds are in the final loop?

The coding round in the final loop can include domain-relevant problems. One candidate received a physics-based collision simulation problem involving diagrams, far more practical than a standard LeetCode question and significantly harder to prepare for with generic study materials. The candidate reported spending more time than expected clarifying the problem because it was so different from typical algorithm questions.

The ML coding round tests hands-on ability with data manipulation. One candidate was given 3D trajectory data and had to manipulate it using numpy to tokenize positions and predict the next step.

The key skills are knowing the numpy API cold: calculating means across multi-dimensional vectors, broadcasting, and reshaping. If you're coming from an ML engineering background, this round should feel comfortable; it's where software engineers tend to struggle.

The ML system design round is largely conversational. One candidate was asked to design a system to retrieve similar driving scenes from a massive video database (for example, "find all scenes with rainy conditions"). The practical application is building training datasets for autonomous driving models by sampling relevant data from a large video collection.

The interviewer cared more about the discussion than written notes. Follow a structured framework, and pay attention to the interviewer's follow-up questions, as they're steering you toward what matters.

The leadership behavioral round is a 45-minute project deep dive. Pick your most impactful project and walk through it in detail. Waymo's interviewers go deep on both the technical challenges and the coordination aspects. They'll ask technical follow-ups about your architecture decisions, not just how you managed stakeholders.

A good strategy: provide a high-level overview first, then let the interviewer steer into the area they care about most. Don't over-prepare a rigid script.

The general behavioral round covers conflict resolution, mentorship, cross-team influence, and "Why Waymo?" Expect questions about how you influence teams that have a dependency on your work but don't report to you.

Waymo Interview Questions

These are examples of real interview questions asked at Waymo. Browse more with our Waymo interview question bank.

Coding

Create a model of a company org chart and search the model based on names, job titles, and teams. (BFS/DFS)
Using a diagram of several obstacles, figure out how they will collide and what the outcome might look like.
Find the sum of all elements in a binary tree that fall within a given range.
Find the container with the maximum volume of water.
Given an unsorted array, find duplicate elements in constant time without using built-in Python functions.

Machine Learning

Given 3D trajectory data, manipulate it using numpy to tokenize positions and predict the next step.
Can you implement batch normalization using NumPy?
How would you determine the right criteria for when to forget outdated data, update the model, and evaluate performance?
Design a post-accident algorithm for a self-driving car.

System Design (ML)

Design a system to retrieve similar driving scenes from a massive video database. Focus on data sampling, embedding approaches, and similarity search.
Design an ML experiment tracking and analysis platform.
Design a language detection system.
Design a newsfeed algorithm for Google.

Behavioral

Walk me through your most impactful project. What was the technical challenge? How did you structure your team?
Tell me about a time you had a conflict with a partner team. How did you resolve it?
How do you approach differences in working with junior and senior engineers on your team?
Tell me about a time you convinced someone to change their mind.
Why Waymo?

Tips for Getting Hired at Waymo

Don't underprepare for coding. The biggest trap for ML engineering candidates is assuming the coding bar is lower than a software engineering role. It isn't. Two of the five or six final round interviews are pure coding (DSA plus ML coding). If you overprepare for ML and underprepare for algorithms, you might not make it past the initial screen.

Be fluent in numpy. The ML coding round tests hands-on ability with data manipulation: means across multi-dimensional vectors, broadcasting, reshaping. Know the numpy API cold.

Treat the ML system design round as a conversation. Waymo interviewers care more about how you think through tradeoffs than about writing everything on a board. Keep high-level notes, but focus on engaging in dialogue. Follow a structured framework, and pay attention to the interviewer's follow-up questions, as they're steering you toward what matters.

Prepare one deep project story. The leadership behavioral round is a 45-minute deep look at a single project. Choose the project with the biggest impact, longest duration, and most cross-team coordination. Be ready to explain both the technical architecture and the organizational challenges. Practice with our mock interview tools to refine your storytelling.

Clarify "coding round" with your recruiter during the prep call. Ask explicitly what type of coding each round involves and whether you'll need numpy, PyTorch, or basic Python. The recruiter may not volunteer this distinction, and it changes your prep plan entirely.

Frequently Asked Questions

Does Waymo hire new graduates?

Yes. Waymo has internship and new grad programs, particularly in software engineering and ML engineering. You can see current openings on the Waymo early careers page.

Does Waymo offer remote positions?

Waymo follows Alphabet's hybrid work model. Most engineering roles are based in the Bay Area with some flexibility for hybrid schedules. Depending on the role, they may support in-person, hybrid, or remote work.

Can I reapply to Waymo if I'm rejected?

Yes. Standard Alphabet reapplication policies generally allow candidates to reapply after 6 to 12 months, depending on the outcome.

Is Waymo's interview process conducted virtually?

Both virtual and in-person options are typically available. Candidates can spread the final loop across multiple days for scheduling flexibility.

Does Waymo provide interview feedback?

Limited. Waymo generally follows Alphabet's practice of providing pass or fail decisions without detailed feedback.

Prepare for Your Waymo Interview

Review recently asked Waymo interview questions and answers from real candidates.
Practice with our mock interview tools.
Prepare for ML engineering interviews with our machine learning engineer course.
Sharpen your system design skills with our system design interview course.

Waymo Posts

Read our latest blog posts about Waymo on Exponent.

Get a Job at Waymo: Interview Process and Top Questions

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