Waymo · Software Engineer
Updated · 2026-09-22

Waymo Software Engineer
Interview Guide

THE 60-SECOND BRIEF

As a Software Engineer at Waymo, you are directly responsible for building and scaling the "Waymo Driver"—the autonomous driving technology powering fully driverless ride-hailing and commercial transport. Your work sits at the intersection of cutting-edge artificial intelligence, high-performance computing, real-time embedded systems, and safety-critical engineering. Engineers in this role build the systems that allow autonomous vehicles to perceive complex environments, predict agent behaviors, navigate dynamic road conditions, and safely transport passengers across major metropolitan areas. The engineering impact at Waymo spans both onboard vehicle systems and offboard support infrastructure. Onboard, you may develop low-latency C++ motion planners, real-time perception models, telematics Linux gateways, or hardware control loops operating under strict execution budgets.

This guide is scoped to a Software Engineer candidate at Waymo.

Waymo candidates report 4 rounds over 3-5 weeks. The stages below are what candidates describe, not a published process.

C++System DesignEdge Case Handling

24 min read

Practice 22 Software Engineer prompts
29Company bank questionsSnapshot · Sep 23, 2026 PT
11Candidate experiences ↗Read their reports
22Practice promptsAcross five skill areas

As a Software Engineer at Waymo, you are directly responsible for building and scaling the "Waymo Driver"—the autonomous driving technology powering fully driverless ride-hailing and commercial transport. Your work sits at the intersection of cutting-edge artificial intelligence, high-performance computing, real-time embedded systems, and safety-critical engineering. Engineers in this role build the systems that allow autonomous vehicles to perceive complex environments, predict agent behaviors, navigate dynamic road conditions, and safely transport passengers across major metropolitan areas. The engineering impact at Waymo spans both onboard vehicle systems and offboard support infrastructure. Onboard, you may develop low-latency C++ motion planners, real-time perception models, telematics Linux gateways, or hardware control loops operating under strict execution budgets. Offboard, you may design distributed Python machine learning pipelines, multi-modal auto-labeling infrastructure, or massive simulation systems capable of testing billions of driving scenarios against real-world sensor logs. This position requires a unique blend of core computer science fundamentals, system design capability, and domain curiosity.

01

Recruiter Screen

reported

Initial assessment of your background and alignment with open roles.

What to demonstrate

  • Initial assessment of your background and alignment with open roles
  • Depth in C++

How to prepare

  • Be able to walk your CV end to end in two minutes, and say why this company specifically.
  • Have your salary expectations, notice period and location constraints ready, and ask for the rest of the loop in writing.
Waymo Software Engineer candidate reports
02

Technical Phone Screen

reported

Coding question shared via a collaborative editor to verify core CS fundamentals.

What to demonstrate

  • Coding question shared via a collaborative editor to verify core CS fundamentals
  • Depth in C++

How to prepare

  • Be able to walk your CV end to end in two minutes, and say why this company specifically.
  • Have your salary expectations, notice period and location constraints ready, and ask for the rest of the loop in writing.
Waymo Software Engineer candidate reports
03

Virtual Onsite Loop

reported

Consists of 4 to 5 rounds, including coding interviews, system design, and behavioral interviews.

What to demonstrate

  • Consists of 4 to 5 rounds
  • Including coding interviews, system design, and behavioral interviews

How to prepare

  • Answer aloud and timed: Given a set of node coordinates and connectivity requirements, traverse a graph structure using suitable graph algorithms to process dynamic spatial data.
  • Answer aloud and timed: Design a high-throughput, low-latency distributed inference platform capable of hosting both internal deep learning models and large language models (LLMs) for bulk evaluation.
Waymo Software Engineer candidate reports
04

Domain Knowledge Round

reported

For specific roles, this round focuses on domain knowledge relevant to the position.

What to demonstrate

  • For specific roles, this round focuses on domain knowledge relevant to the position
  • Depth in C++

How to prepare

  • Answer aloud and timed: Architect a real-time telematics data pipeline to handle continuous sensor logging, vehicle state telemetry, and over-the-air (OTA) updates for a large autonomous fleet.
  • Answer aloud and timed: Design an object-oriented system for differential scene evaluation or autonomous scenario generation.
Waymo Software Engineer candidate reports

11 candidate reports. Individual accounts describe a particular role and hiring cycle.

Software Engineer

Waymo Software Engineer Interview Experience — Navigation Constraints and Mapping Systems

Technical Screen → Onsite

The author lists a Waymo phone screen followed by onsite system-design and coding interviews. The screen involved a robot moving in four directions, returning to its starting point, and avoiding obstacles. The design discussion asked about a vehicle fleet collecting map information. One onsite coding task matched dictionary words against input containing repeated letters. Another used a map with…

Read full experience
Software Engineer

Waymo Software Engineer Interview Experience — A Simulation Design Round After a Recruiter Reassurance

OnsiteOutcome: rejected

Coding: 317. The second problem was traversing a graph with DFS, fairly simple. There was a follow-up: come up with an algorithm to prove your answer is correct. A strange follow-up. Behavioral: Very standard. A project I'm proud of, how to handle priorities, things like that. System design: This was the first round of the interview. What a disastrous start. I was interviewing with the simulation…

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Site Reliability Engineer

Waymo Site Reliability Engineer Interview Experience — Rejected After a Rough, Disrespectful Technical Screen

Technical ScreenOutcome: rejected

I got rejected. This interview was for an SRE (Site Reliability Engineer) role. The question was roughly this: there's a number line from 0 to 50. Points keep landing on the line, and each point contaminates the region 0.5 to its left and 0.5 to its right of where it lands — i.e., an interval of length 1. Once part of the line is contaminated, it stays contaminated forever. Points can land anywhe…

Read full experience

PracHub editorial advice for the preparation topics above.

01

Going into the loop without having done this.

Clarify assumptions early in algorithmic problems: Interviewers at Waymo often present open-ended or slightly ambiguous coding prompts. Do not jump straight into writing code; actively state your assumptions, ask clarifying questions about inputs and constraints, and propose counter-examples before writing your solution.

02

Going into the loop without having done this.

Brush up on C++ language fundamentals: If you choose C++ for your coding rounds or are applying to onboard teams, ensure you are comfortable with modern features, smart pointers, memory management, and standard library data structures. Avoid over-complicating solutions with unnecessary templates when simple structures work cleanly.

03

Going into the loop without having done this.

Be ready for domain-specific math questions: Even in standard software engineering loops, candidates are occasionally asked basic physics, matrix math, or kinematics questions (such as calculating stopping distances or coordinate transformations). Review basic physics formulas and vector operations during your preparation.

04

Going into the loop without having done this.

Avoid spending too much time explaining high-level concepts at the expense of completing the live code. Waymo interviewers expect candidates to write working, complete, or near-complete code solutions within the allotted 45-minute window.

Choose a category, try a prompt, then open its approach, worked solution or follow-up when you need it.

19 technical prompts0 include a worked solution

Implement a multi-source Breadth-First Search (BFS) algorithm to randomly populate an $m \times n$ grid with d

medium
Data Structures & Algorithms

Implement a multi-source Breadth-First Search (BFS) algorithm to randomly populate an $m \times n$ grid with distinct tokens while ensuring each token group remains contiguous.

Approach
  1. Restate the input: its shape, its size, and what is guaranteed about it.
  2. Name the brute-force solution and its complexity before improving on it.
  3. Choose the data structure from the access pattern, not from familiarity.
  4. State the target complexity and say which constraint rules the naive version out.
Follow-up
  • How does this change if the input no longer fits in memory?
  • What is the worst case, and how likely is it on real data?

Write an algorithm to traverse a 2D matrix, calculate recursive cell weights, and return optimized path parame

medium
Data Structures & Algorithms

Write an algorithm to traverse a 2D matrix, calculate recursive cell weights, and return optimized path parameters under strict time constraints.

Approach
  1. Restate the input: its shape, its size, and what is guaranteed about it.
  2. Name the brute-force solution and its complexity before improving on it.
  3. Choose the data structure from the access pattern, not from familiarity.
  4. State the target complexity and say which constraint rules the naive version out.
Follow-up
  • How does this change if the input no longer fits in memory?
  • What is the worst case, and how likely is it on real data?

Solve a string dynamic programming problem focused on pattern matching and sequence alignment.

medium
Data Structures & Algorithms

Solve a string dynamic programming problem focused on pattern matching and sequence alignment.

Approach
  1. Restate the input: its shape, its size, and what is guaranteed about it.
  2. Name the brute-force solution and its complexity before improving on it.
  3. Choose the data structure from the access pattern, not from familiarity.
  4. State the target complexity and say which constraint rules the naive version out.
Follow-up
  • How does this change if the input no longer fits in memory?
  • What is the worst case, and how likely is it on real data?

Given a buggy implementation of a history buffer in C++, identify memory leaks, race conditions, and syntax er

medium
Data Structures & Algorithms

Given a buggy implementation of a history buffer in C++, identify memory leaks, race conditions, and syntax errors, then refactor it for production stability.

Approach
  1. Say what the runtime actually does before reasoning about the code.
  2. Name what is shared across threads and what owns each piece of state.
  3. Identify the window where an invariant is briefly untrue.
  4. Distinguish a value from a reference to it, and say which one you handed out.
Follow-up
  • What happens if two callers reach this at the same time?
  • Where could this allocate more than you expect?

Given a set of node coordinates and connectivity requirements, traverse a graph structure using suitable graph

medium
Data Structures & Algorithms

Given a set of node coordinates and connectivity requirements, traverse a graph structure using suitable graph algorithms to process dynamic spatial data.

Approach
  1. Restate the input: its shape, its size, and what is guaranteed about it.
  2. Name the brute-force solution and its complexity before improving on it.
  3. Choose the data structure from the access pattern, not from familiarity.
  4. State the target complexity and say which constraint rules the naive version out.
Follow-up
  • How does this change if the input no longer fits in memory?
  • What is the worst case, and how likely is it on real data?

Describe how you approach framing an open-ended, ambiguous real-world scenario into a well-defined engineering

medium
Behavioral & Technical Leadership

Describe how you approach framing an open-ended, ambiguous real-world scenario into a well-defined engineering problem.

Approach
  1. Restate the input: its shape, its size, and what is guaranteed about it.
  2. Name the brute-force solution and its complexity before improving on it.
  3. Choose the data structure from the access pattern, not from familiarity.
  4. State the target complexity and say which constraint rules the naive version out.
Follow-up
  • How does this change if the input no longer fits in memory?
  • What is the worst case, and how likely is it on real data?

Built from the rounds and topics Waymo candidates report.

Small steps. Visible outcomes.0 / 7 completed
ONE WEEK · YOUR PACE

Prepare, practise & reflect

One practical outcome each day. Spend longer where you need it.

0 / 7 done
01Map the Waymo loop
  • Write out the reported sequence: Recruiter Screen, Technical Phone Screen, Virtual Onsite Loop, Domain Knowledge Round.
  • For each round, write one sentence on what it is judging, from the description above, and mark the one you are least ready for.

Deliverable: A one-page map of the 4 reported rounds, with the weakest marked.

02Work C++
  • Spend the session on C++, which Waymo candidates report being tested on.
  • Write one worked example in C++ and time yourself on it.

Deliverable: One timed worked example in C++.

03Work System Design
  • Spend the session on System Design, which Waymo candidates report being tested on.
  • Write one worked example in System Design and time yourself on it.

Deliverable: One timed worked example in System Design.

04Work Edge Case Handling
  • Spend the session on Edge Case Handling, which Waymo candidates report being tested on.
  • Write one worked example in Edge Case Handling and time yourself on it.

Deliverable: One timed worked example in Edge Case Handling.

05Answer out loud: Data Structures & Algorithms
  • Answer aloud, timed: Implement a multi-source Breadth-First Search (BFS) algorithm to randomly populate an $m \times n$ grid with distinct tokens while ensuring each token group remains contiguous.
  • Answer aloud, timed: Write an algorithm to traverse a 2D matrix, calculate recursive cell weights, and return optimized path parameters under strict time constraints.

Deliverable: Spoken answers to 2 reported Data Structures & Algorithms question(s), under time.

06Answer out loud: System Design & Infrastructure
  • Answer aloud, timed: Design a high-throughput, low-latency distributed inference platform capable of hosting both internal deep learning models and large language models (LLMs) for bulk evaluation.
  • Answer aloud, timed: Architect a real-time telematics data pipeline to handle continuous sensor logging, vehicle state telemetry, and over-the-air (OTA) updates for a large autonomous fleet.

Deliverable: Spoken answers to 2 reported System Design & Infrastructure question(s), under time.

07Answer out loud: Domain-Specific & Machine Learning Engineering
  • Answer aloud, timed: Explain the mathematical and structural trade-offs between classification and regression loss functions when modeling agent trajectory prediction.
  • Answer aloud, timed: Implement geometric computer vision concepts in C++, such as vector cross products and nearest-neighbor point cloud searching algorithms.

Deliverable: Spoken answers to 2 reported Domain-Specific & Machine Learning Engineering question(s), under time.

Expand any day for tasks and deliverables. Your progress is saved on this device.

Behavioural rounds judge the decision you made and what it cost.

Tell me about a time you had a technical disagreement with a colleague regarding software design and how you r

medium
Behavioral & Technical Leadership

Tell me about a time you had a technical disagreement with a colleague regarding software design and how you resolved it.

Approach
  1. Pick a story where you made the decision, not one where you watched it.
  2. State the situation in two sentences and spend the rest on the reasoning.
  3. Give the blast radius: what could have broken, and what you measured.
  4. Name the disagreement and how you resolved it with evidence.
Follow-up
  • What would you do differently if you ran that again?
  • How did you know your change caused the improvement?

How do you balance the trade-off between pushing new features quickly and maintaining long-term code health in

medium
Behavioral & Technical Leadership

How do you balance the trade-off between pushing new features quickly and maintaining long-term code health in a mission-critical codebase?

Approach
  1. Pick a story where you made the decision, not one where you watched it.
  2. State the situation in two sentences and spend the rest on the reasoning.
  3. Give the blast radius: what could have broken, and what you measured.
  4. Name the disagreement and how you resolved it with evidence.
Follow-up
  • What would you do differently if you ran that again?
  • How did you know your change caused the improvement?

Estimate work you have never done and defend the range

hard
estimationbackfillsexpand-contract

You are asked to estimate a change you have never attempted: add a column to a 100-million-row table, populate it, move reads across, and drop the old shape. Give a range with the assumptions that generate it, including batch size, the signal your backfill throttles on, and wall-clock hours, and name the three unknowns that would move the number most. Then describe a real estimate you gave under comparable ignorance: how you expressed its uncertainty, what you committed to, and how wrong you turned out to be.

Approach
  1. Decompose into independently deployable steps before estimating anything: add the column nullable, write both shapes, backfill in batches, verify, move reads, stop writing the old shape, drop it. That is four deploys spread over days, and the calendar estimate is dominated by them rather than by the loop's runtime.
  2. Do the arithmetic aloud for the part that has arithmetic in it: batch size times number of batches times per-batch duration, at a write rate the primary can absorb alongside roughly 1.2k writes per second of production traffic. The loop is throttled by replication lag and lock waits, not by how fast it can issue statements.
  3. Price the schema step by its lock rather than its statement duration. In PostgreSQL an ALTER TABLE taking ACCESS EXCLUSIVE waits for every open transaction on that table while later queries queue behind it, so a millisecond change issued during a thirty-second analytics query stalls that table for thirty seconds. Adding a nullable column with a non-volatile default avoids a rewrite from version 11; a new index wants CREATE INDEX CONCURRENTLY, which cannot run inside a transaction block and leaves an invalid index behind if it fails.
  4. Express the answer as a range whose endpoints each trace to a stated assumption, then name the cheapest experiment that collapses it, which is almost always running one real batch against the real table and multiplying.
Follow-up
  • How do you verify the backfill genuinely finished, given rows written by production traffic while it ran?
  • Where does the backfill resume from after a worker is killed mid-batch, and what makes that resume point trustworthy?
  • 01

    Tell me about a time you had a technical disagreement with a colleague regarding software design and how you resolved it.

  • 02

    How do you balance the trade-off between pushing new features quickly and maintaining long-term code health in a mission-critical codebase?

  • 03

    You are asked to estimate a change you have never attempted: add a column to a 100-million-row table, populate it, move reads across, and drop the old shape. Give a range with the assumptions that generate it, including batch size, the signal your backfill throttles on, and wall-clock hours, and name the three unknowns that would move the number most. Then describe a real estimate you gave under comparable ignorance: how you expressed its uncertainty, what you committed to, and how wrong you turned out to be.

PracHub preparation framework
How difficult are the coding interviews at Waymo compared to other tech companies?

The coding interviews at Waymo are technically demanding and generally range from LeetCode medium to hard difficulty. Beyond basic algorithmic accuracy, interviewers place a heavy emphasis on edge-case handling, clean code syntax, correct language usage (especially in C++), and your ability to write compilable, well-structured logic under time pressure.

Waymo Software Engineer candidate reports
Do I need prior experience in robotics or autonomous vehicles to get hired?

No, prior autonomous vehicle or robotics experience is not strictly required for general Software Engineer roles. While domain knowledge in perception, planning, or kinematics is beneficial, Waymo frequently hires top-tier software engineers with strong computer science fundamentals, distributed systems experience, or solid machine learning backgrounds.

Waymo Software Engineer candidate reports
What programming languages am I allowed to use during the interview?

For general coding rounds, you are typically allowed to use your language of choice, such as C++, Python, or Java. However, for specialized roles—such as Onboard Infrastructure or Telematics—interviewers may require live coding specifically in C++ to evaluate language-specific memory management and system knowledge.

Waymo Software Engineer candidate reports
How does the team matching phase work at Waymo?

After passing the virtual onsite technical evaluation, candidates enter the team matching phase. During this stage, recruiters connect you with hiring managers across different teams (e.g., Planner, Perception, ML Platform) to discuss specific team mandates, projects, and working styles. Once a mutual match is confirmed, the formal offer approval process moves forward.

Waymo Software Engineer candidate reports
What is the work location policy for Software Engineers at Waymo?

Most engineering roles at Waymo follow a hybrid work model requiring team members to be in-office several days a week, primarily located in Mountain View, CA, San Francisco, CA, or Sunnyvale, CA. Specific remote or hybrid flexibilities depend on the team, particularly for offboard tools and platform positions.

Waymo Software Engineer candidate reports
How hard is the Waymo interview?

Candidates most commonly rate Waymo interviews as medium, based on 458 reported interviews. About 25% of candidates who interview go on to receive an offer.

Waymo Software Engineer candidate reports
What topics does Waymo test in interviews?

Waymo interviews most often cover C++, SQL, Cross-Functional Collaboration, Go-to-Market (GTM) Strategy, and Data-Driven Decision Making. The exact emphasis depends on the specific role you apply for.

Waymo Software Engineer candidate reports
Is Waymo a good place to work?

Employees rate Waymo 3.9 out of 5 overall, based on aggregated workplace reviews spanning career growth, work-life balance, compensation, culture, and management.

Waymo Software Engineer candidate reports
Sources & methodology 3 sources ↗

Official role evidence, timestamped platform data and clearly labeled preparation advice.