Practice real interview problems from Waymo
| Status | Title | Solution | Practice | Difficulty | Companies | Topics |
|---|---|---|---|---|---|---|
| 10. Regular Expression Matching | Solution | Solve | Hard | Accenture+26 | ||
| 68. Text Justification | Solution | Solve | Hard | Airbnb+39 | ||
| 84. Largest Rectangle in Histogram | Solution | Solve | Hard | Adobe+31 | ||
| 149. Max Points on a Line | Solution | Solve | Hard | Amazon+15 | ||
| 317. Shortest Distance from All Buildings | Solution | Solve | Hard | Amazon+12 | ||
| 631. Design Excel Sum Formula | Solution | Solve | Hard | Airbnb+8 | ||
| 871. Minimum Number of Refueling Stops | Solution | Solve | Hard | Amazon+7 | ||
| 1944. Number of Visible People in a Queue | Solution | Solve | Hard | Amazon+14 |
Waymo, Alphabet's autonomous driving company, hires engineers who can build highly reliable and scalable systems that operate in real‑world environments. Because their products power self‑driving vehicles, the engineering culture emphasizes strong fundamentals, clean problem solving, and the ability to reason about edge cases. The Waymo coding interview reflects this focus by testing deep understanding of data structures, algorithms, and practical engineering trade‑offs.
The typical Waymo interview process begins with a recruiter screen followed by a technical phone interview focused on algorithmic coding. Candidates who pass usually move to a multi‑round onsite (or virtual onsite) where engineers evaluate coding ability, problem solving, and system design skills. Many of the questions resemble high‑quality LeetCode problems but often require careful reasoning about correctness and performance.
Across real interviews, Waymo tends to emphasize:
The overall difficulty distribution usually includes a mix of medium and hard questions, with a strong emphasis on writing clean and correct code rather than solving trick puzzles.
FleetCode helps you prepare with a curated set of 18 real Waymo interview questions asked in coding rounds. Each problem includes detailed explanations and solutions in Python, Java, and C++. By practicing these patterns and learning the reasoning behind them, you can approach the Waymo coding interview with confidence.
Preparing for a Waymo coding interview requires more than just solving random algorithm problems. The company evaluates how clearly you reason about algorithms, edge cases, and system constraints—skills that are critical for building reliable autonomous driving software.
Typical Waymo interview format:
Most coding rounds expect you to write production‑quality code and explain your reasoning step by step.
Common problem categories asked at Waymo:
These topics reflect the types of computational challenges that appear in robotics, mapping, and large‑scale data processing.
Preparation strategy:
Common mistakes to avoid include jumping into coding without discussing the approach, ignoring edge cases, and failing to test the solution with examples. Interviewers expect you to communicate clearly and iterate on your solution.
A good preparation timeline is 6–8 weeks. Spend the first few weeks strengthening algorithm fundamentals, then practice company‑specific problems like the 18 curated Waymo questions on FleetCode. Simulating real interview conditions—solving problems within 30–40 minutes—can make a big difference in performance during the actual interview.