Recently, Waymo announced its expansion of autonomous taxi services to more cities. This news led to a sharp decline in Uber and Lyft's stock prices, raising concerns about intensified competition in the ride-hailing industry. As a leader in autonomous driving technology, Waymo not only dominates the market but also sets a high bar for talent selection. Want to join Waymo? Take a look at how their algorithm interviews challenge candidates!

Waymo’s technical interviews heavily emphasize algorithmic proficiency, particularly in dynamic programming, greedy algorithms, and search-based problems. Below are some of the latest Waymo interview questions, which assess how candidates maximize scores within limited steps—an approach directly applicable to decision optimization in autonomous driving.

Q1. You have an array containing N elements and each element has a score. In each step, you can pop an element from the leftmost or the rightmost position of the array, and gain a score from the element you choose. What is the maximum aggregated score you can obtain after K steps?

This problem seems straightforward but actually tests dynamic programming + sliding window thinking. The key is to determine the optimal strategy within K moves—not greedily choosing the highest score at each step nor blindly exploring all possible paths. With CSOAHelp’s guidance, the candidate quickly identified the optimal approach.

CSOAHelp's guidance:

• Prefix Sum + Two Pointers: Compute the sum of the first i elements on the left and the first j elements on the right, ensuring i + j = K, then iterate through all possible (i, j) pairs to find the maximum score.
• Dynamic Programming: Use dp[i][j] to store the maximum score obtained by taking i elements from the left and j elements from the right.
• Time Complexity: O(K), as only K possibilities need to be considered, avoiding brute force approaches.

Following these instructions, the candidate systematically explained their approach and successfully implemented the solution. The interviewer acknowledged the candidate’s logical clarity and implementation skills.

Q2. You have another array M with K weights. Each time you made the ith pop in Q1, multiply the score of the chosen element with the weight in M[i]. What is the maximum score you can get?

This problem builds upon Q1 by introducing weight multipliers, adding an extra layer of complexity. The challenge is to strategically assign values from M[i] to maximize the final score while avoiding suboptimal pairings.

CSOAHelp's guidance:

• Greedy + Dynamic Programming: The largest weight should be assigned to the highest score, meaning weight and score should be sorted before pairing.
• Deque Optimization: Use a deque to maintain the available score values dynamically, ensuring that each weight is paired with the best possible score at that moment.
• Time Complexity: O(K log K), due to sorting operations, but remains computationally efficient.

With CSOAHelp's real-time guidance, the candidate implemented the solution correctly and justified why a greedy approach ensures an optimal outcome. The interviewer followed up with a question: If weight values vary significantly, would the greedy strategy still work? CSOAHelp prompted the candidate: In extreme cases (e.g., when weight values have drastic differences), a dynamic programming approach might be necessary instead of a simple greedy algorithm. The candidate repeated this reasoning, illustrated with examples, and received positive feedback from the interviewer.

As a subsidiary of Alphabet, Waymo sets a high bar for algorithm engineers. These interview problems not only assess fundamental algorithmic skills but also test optimization, decision-making, and dynamic programming—all crucial for real-world scenarios like path planning and optimal driving strategies.

For aspiring Waymo engineers, mastering dynamic programming, greedy algorithms, and search-based methods is essential, along with optimization problem-solving skills to determine the best solutions under different constraints. This interview success further demonstrates CSOAHelp’s invaluable role—providing real-time structured guidance to help candidates effectively showcase their abilities in high-stakes interviews.

Waymo’s rigorous interview process reflects its technical leadership. If you’re aiming to join this industry giant, are you prepared for complex algorithmic challenges? CSOAHelp ensures you're ready to tackle even the toughest interviews, making sure your technical skills align with Waymo’s high hiring standards!

经过csoahelp的面试辅助，候选人获取了良好的面试表现。如果您需要面试辅助或面试代面服务，帮助您进入梦想中的大厂，请随时联系我。

If you need more interview support or interview proxy practice, feel free to contact us. We offer comprehensive interview support services to help you successfully land a job at your dream company.