Recently helped a student ace the *WeRide * virtual interview for an autonomous driving algorithm position. The whole process was quite practical — not overly theoretical like some international companies. Below is a detailed recap of the interview structure, technical focus, and key takeaways.
🧩 Interview Overview
WeRide’s interview process usually consists of two Virtual Interviews (VO) plus one technical evaluation, mainly assessing:
- Coding ability (Python / C++ + algorithm implementation)
- Data analysis and modeling (especially for perception / localization / planning modules)
- Project deep dive (technical decision-making & trade-off discussions)
The student I coached applied for an Algorithm R&D position focusing on Perception, with the total VO lasting around 90 minutes.
🧑💻 Round 1: Coding + Debugging
The first round focused purely on hands-on coding, conducted on a platform similar to HackerRank. The problems were closely tied to real-world autonomous driving engineering.
🧠 Problem 1: Path Planning Simplification
Given a 2D grid with obstacles, implement a simplified version of A* pathfinding that returns the shortest path from start to goal.
Key points:
- Core BFS / A* logic
- Proper use of priority queue (
heapq) - Boundary checks and
visitedset management - Time complexity around O(n log n)
The interviewer also followed up with:
“How would you update the path dynamically if the obstacles change in real time?”
That question tests incremental planning knowledge — how to adapt pathfinding to dynamic environments.
📊 Problem 2: Sensor Data Filtering
Given a list of noisy sensor readings, design a filter that smooths the output using a sliding window average.
A small but elegant problem blending signal processing and coding.
Focus areas:
- Implementing a sliding window or prefix sum for O(n) performance
- Handling window edges and data normalization
🧠 Round 2: System Design + Project Deep Dive
This round was more application-oriented, digging into the candidate’s resume projects.
The student had worked on LiDAR-based object detection, so the interviewer asked:
- Why choose PointPillars over CenterPoint?
- How much latency reduction did you get after model quantization?
- What deployment challenges occur on low-power edge devices?
Then it extended into system-level thinking:
“If you were to integrate the detection module into the full perception pipeline, how would you design inter-module communication and latency control?”
👉 Tip: Be ready to discuss your project from three angles — tech stack, model architecture, and deployment results. Otherwise, you risk being cornered on implementation details.
🎯 Interviewer Style
WeRide interviewers are very experienced, especially in perception and planning. They can tell instantly if you’re just reciting or truly understand the concepts.
Don’t give generic, memorized answers — instead, use real project metrics and specific examples to show depth.
🗣️ Programhelp Real-Time Support
During this session, our student used Programhelp’s real-time voice assistance system:
- When they got stuck on A*’s heuristic design, we provided a quick hint via voice.
- During project discussion, we guided them to highlight trade-offs and quantitative results, which impressed the interviewer.
As a result, they smoothly advanced to the system design round, with the interviewer praising their “clear logic and practical insights.”
If you’re preparing for autonomous driving interviews (WeRide / Cruise / Zoox / Motional / Waymo, etc.),
Programhelp offers undetectable remote assistance + real-time voice coaching, helping you perform confidently and accurately — without disrupting the platform environment.
💬 FAQ
Q1: What languages are used in the interview?
Mainly Python or C++, depending on the team. Perception focuses on Python; Planning leans toward C++.
Q2: How hard are the coding problems?
Medium difficulty — not LeetCode Hard, but clarity and completeness are crucial.
Q3: Do I need ROS or Autoware experience?
It’s a plus. Experience with ROS nodes, bag file replay, or module communication design makes you stand out.
Q4: Is the interview in English?
Most technical interviews are in Chinese, but your resume and any slides should be in English.
📎 Summary
WeRide interviews emphasize applied engineering ability rather than theoretical depth.
If you can communicate your algorithms through practical deployment results and trade-off reasoning, you’ll have a clear advantage.
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