Waymo Machine Learning Engineer Interview Questions + Guide in 2024

Waymo, an industry leader in autonomous driving technology, started its journey as the Google Self-Driving Car Project in 2009. The company envisions becoming the most trusted driver while improving access to mobility and saving lives lost to traffic crashes. The Waymo Driver has provided over one million autonomous rider-only trips across 13+ U.S. states and continues to redefine transportation.

The Machine Learning Engineer position is critical to the organization, particularly on the ML Infrastructure and Platform teams. These teams collaborate closely with research and production units to develop cutting-edge models in perception and planning, essential for Waymo’s autonomous driving software.

This guide will walk you through the interview process, commonly asked Waymo machine learning engineer interview questions and tips for success. Let’s get started!

The interview process usually depends on the role and seniority; however, you can expect the following on a Waymo machine learning engineer interview:

Recruiter/Hiring Manager Call Screening

If your application catches the recruiter’s attention, you will be contacted for an initial screening call. During this call, the recruiter will validate your experience, skill set, and overall fit for the company. Expect to discuss your background, interest in Waymo, and some basic technical skills pertinent to the role.

This call typically lasts 30-45 minutes and may also introduce foundational behavioral questions. It provides an opportunity for you to ask questions about Waymo and the specific role you applied for.

Technical Virtual Interview

Succeeding in the initial screening call leads to an invitation for a technical interview. This stage often involves a 45-minute coding interview conducted virtually. You may be required to complete coding challenges that test your proficiency in Python or C++ and your understanding of machine learning frameworks like TensorFlow or PyTorch.

Prepare to solve problems related to distributed systems, performance optimization, and machine learning model deployment. Depending on the position’s seniority, additional rounds may involve discussing your approach to collaborative problem-solving, technical design, and your ability to troubleshoot complex systems.

Onsite Interview Rounds

After passing the technical virtual interview, you will be invited to onsite interviews at Waymo’s office. This comprehensive stage consists of several rounds, focusing on both technical and behavioral aspects:

1. Multiple Coding and Design Interviews: These interviews further assess your coding skills, system design capabilities, and problem-solving approach.
2. Deep Technical Interviews: Expect questions about your experience with machine learning models, distributed training algorithms, and scalable infrastructure components.
3. Behavioral and Situational Interviews: These interviews gauge your ability to work within a team, handle challenges, and your overall cultural fit with Waymo.
4. Presentation of Take-Home Exercises: If you were previously given technical assignments or case studies, you may be asked to present your solutions and discuss your approach.

Typically, interviews at Waymo vary by role and team, but commonly, Machine Learning Engineer interviews follow a fairly standardized process across these question topics.

1. How would you improve Google Maps?

As the PM on Google Maps, what feature improvements would you implement? What metrics would you check to see if these improvements are successful?

2. What factors could have biased Jetco’s boarding time study results?

Jetco’s study showed the fastest average boarding times. What factors could have biased this result, and what would you investigate?

3. How would you decrease tech debt and developer turnaround time at a fintech startup?

Management has raised concerns about increased developer hours due to tech debt. How would you address and reduce tech debt to improve developer turnaround time?

4. How would you design an incentive scheme for Uber drivers to enter high-demand city areas?

Working on the Uber app, how would you create an incentive scheme to encourage drivers to enter city areas with high demand?

5. Customer success manager vs. free trial for Square’s new software product?

As the head of Square’s small business division, would you recommend hiring a customer success manager or instituting a free trial to get new or existing customers to use a new software product? Explain your recommendation.

6. What metrics and statistical methods would you use to identify dishonest users in a sports app?

You work for a company with a sports app that tracks running, jogging, and cycling data. To identify dishonest users, such as those driving a car while claiming to bike, what metrics (e.g., distance, pace, splits, elevation gain, heart rate) would you analyze, and what statistical methods would you use to detect athletic anomalies?

7. Write a function digit_accumulator to sum every digit in a floating-point number string.

You are given a string that represents some floating-point number. Write a function, digit_accumulator, that returns the sum of every digit in the string.

8. Create a function to find the nearest common ancestor of two nodes in a binary tree.

You are given a binary tree of unique positive numbers. Each node in the tree is implemented as a dictionary with the keys left and right, indicating the node’s left and right neighbors, respectively, and data that holds an integer value. Given two nodes as input (value1 and value2), write a function to return the value of the nearest node that is a parent to both nodes. If one of the nodes doesn’t exist in the tree, return -1.

9. Develop a function to determine the robot’s path in a 4x4 matrix.

A robot has been designed to navigate a two-dimensional 4x4 matrix by only moving forward or turning right when blocked by a wall. Its starting position is in the top left corner of the matrix, denoted by (0,0), and the robot’s final destination is in the bottom right corner. Determine the full path of the robot before it hits the final destination or starts repeating the path.

10. How would you evaluate a method or algorithm to match users with their siblings on Facebook?

A Facebook product manager has asked you to develop a method for matching users to their siblings. How would you evaluate the effectiveness of this method or algorithm, and what metrics might you use?

To maximize your chances of success in a Waymo interview, consider the following tips:

1. Understand the Autonomous Driving Domain: Waymo works at the cutting edge of autonomous driving technology. Thoroughly research the company’s mission, its products, and the technology stack it uses. Be prepared to discuss how your expertise can contribute to their goals.

2. Brush Up on System Design and ML Frameworks: Waymo’s interview process emphasizes your ability to design distributed systems and optimize machine learning models. Make sure to review key concepts and practice relevant problems in Python, C++, TensorFlow, and PyTorch.

3. Emphasize Collaboration and Innovation: Waymo values innovation and collaboration. Practice articulating your experiences with team-based projects, how you tackle collaborative challenges, and your contributions to innovative solutions in previous roles.

By thoroughly preparing and showcasing your relevant skills and passion for autonomous driving technology, you can set yourself up for a successful interview experience with Waymo. Good luck!

What is the average salary for a Machine Learning Engineer at Waymo?

What projects will I work on as a Machine Learning Engineer at Waymo?

At Waymo, you’ll be part of the ML Platform team, developing models and tools that enhance TensorFlow and JAX and address challenges like scalability, performance, and reliability. Your work will involve optimizing neural network architectures, distributed training, and improving the developer experience of Waymo’s scalable ML framework.

What qualifications are needed for the Machine Learning Engineer position at Waymo?

A BS in Computer Science, Math, or equivalent experience is required, as strong skills in Python or C++ and experience with ML frameworks like TensorFlow or PyTorch. Additional experience with distributed systems, ML accelerator profiling tools, and cloud computing platforms is preferred.

What is the company culture like at Waymo?

Waymo fosters an innovative and inclusive environment, valuing creativity, collaboration, and diversity. You’ll work alongside world-class engineers and scientists, with ample personal and professional growth opportunities.

What are the benefits of the Machine Learning Engineer position at Waymo?

Waymo offers discretionary annual bonuses, equity incentives, and a comprehensive benefits package. This includes medical, dental, vision insurance, mental wellness support, paid parental leave, and access to Google offices and amenities.

As the autonomous driving industry innovates, Waymo is at the forefront of seeking passionate and skilled machine learning engineers. By diving into the intricacies of scalable models, distributed training systems, and advanced ML frameworks, you will play a crucial role in developing the world’s most trusted driver.

Stay prepared by focusing on the essential skills and experiences highlighted, and be ready to showcase your expertise in collaboration, optimization, and problem-solving during the interview process.

Explore Waymo’s main interview guide, and join their mission of improving access to mobility while saving lives. Good luck with your interview journey at Waymo!