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ML Engineer, Foundation Model Evaluation

Waymo is an autonomous driving technology company with the mission to be the most trusted driver. Since its start as the Google Self-Driving Car Project in 2009, Waymo has focused on building the Waymo Driver—The World's Most Experienced Driver™—to improve access to mobility while saving thousands of lives now lost to traffic crashes. The Waymo Driver powers Waymo One, a fully autonomous ride-hailing service, and can also be applied to a range of vehicle platforms and product use cases. The Waymo Driver has provided over one million rider-only trips, enabled by its experience autonomously driving tens of millions of miles on public roads and tens of billions in simulation across 13+ U.S. states.

The mission of the Waymo Research team is to develop machine learning solutions addressing open problems in autonomous driving, towards the goal of safely operating Waymo vehicles in dozens of cities and under all driving conditions. As part of our work, we also initiate and foster collaborations with other research teams in Alphabet. Research areas that we are currently focusing on include reinforcement learning, learning from demonstration, generative modeling, Bayesian inference, hierarchical learning, and robust evaluation.

In this remote role, you will report to a Principal Research Scientist.

You will:

  • Incorporate and extend cutting edge research in robotics and machine learning to advance the state-of-the-art for evaluating the quality, safety and realism of our embodied AI agents
  • Partner within and across organizations to land disruptive and innovative tech in production
  • Work with a variety of state-of-the-art Foundation Models
  • Leverage our industry-leading datasets and state-of-the-art safety framework to land fleet-wide improvements in model performance

You have:

  • Masters degree in Computer Science, Machine Learning, Robotics, similar technical field of study, or equivalent practical experience
  • Proficiency in Python
  • Familiarity with one of the modern deep learning frameworks (e.g. Pytorch, JAX, Tensorflow)
  • Prior work in an industrial or research setting developing methodologies for the evaluation of ML models

We prefer:

  • Strong hands-on SWE skills, able to design, implement, and extend large scale data and evaluation pipelines
  • Track record of publications in top-tier conferences or leading open source projects in the related fields
  • Proficiency in C++
  • Experience in AV planning and related research

#LI-Remote

Please note that Waymo may not be able to employ remotely in all locations. Please speak with your recruiter about your preferred location for remote work when you begin the interview process.

The expected base salary range for this full-time position across US locations is listed below. Actual starting pay will be based on job-related factors, including exact work location, experience, relevant training and education, and skill level. Your recruiter can share more about the specific salary range for the role location or, if the role can be performed remote, the specific salary range for your preferred location, during the hiring process. 

Waymo employees are also eligible to participate in Waymo’s discretionary annual bonus program, equity incentive plan, and generous Company benefits program, subject to eligibility requirements. 

Salary Range
$170,000$216,000 USD
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Average salary estimate

$193000 / YEARLY (est.)
min
max
$170000K
$216000K

If an employer mentions a salary or salary range on their job, we display it as an "Employer Estimate". If a job has no salary data, Rise displays an estimate if available.

What You Should Know About ML Engineer, Foundation Model Evaluation, Waymo

Waymo is looking for a talented ML Engineer specialized in Foundation Model Evaluation to join our remote team. As a pivotal player in advancing autonomous driving technology, you’ll contribute to making the Waymo Driver, hailed as The World's Most Experienced Driver™, even more reliable and proficient. This is not just a job; it’s an opportunity to be part of a mission that prioritizes safety and accessibility in mobility solutions. Your work will center around cutting-edge research in robotics and machine learning, addressing critical evaluations of our AI agents. You’ll collaborate with teams across organizations, turning innovative designs into groundbreaking tech production while leveraging our extensive datasets and advanced safety frameworks to enhance fleet performance. To succeed in this role, you should have a Master’s degree in fields like Computer Science or Robotics and be proficient in Python, with familiarity in deep learning frameworks such as PyTorch or TensorFlow. If you possess strong software development skills and a knack for designing scalable evaluation systems, you’re exactly who we’re looking for! At Waymo, your research contributions won't just stagnate in academic papers; they’ll be effective solutions in real-world applications. Join us to ensure safe driving experiences for all and become an integral part of a team that pushes the boundaries of what autonomous vehicles can do.

Frequently Asked Questions (FAQs) for ML Engineer, Foundation Model Evaluation Role at Waymo
What responsibilities does an ML Engineer, Foundation Model Evaluation at Waymo have?

An ML Engineer specializing in Foundation Model Evaluation at Waymo is tasked with integrating cutting-edge research in robotics and machine learning to evaluate and improve the performance of our AI models. You will engage in collaborative efforts across teams to translate innovative ideas into practical tech solutions while focusing on enhancing the fleet's performance using our vast datasets.

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What qualifications are required for the ML Engineer position at Waymo?

To apply for the ML Engineer, Foundation Model Evaluation position at Waymo, candidates should have a Master's degree in Computer Science, Machine Learning, Robotics, or a similar technical field, along with proficiency in Python. Familiarity with modern deep learning frameworks, and a background in developing evaluation methodologies for ML models in an industrial or research setting is crucial.

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What programming skills are preferred for the Waymo ML Engineer role?

For the ML Engineer role at Waymo, candidates are preferred to have strong hands-on software engineering skills with experience in designing and extending large-scale data and evaluation pipelines. Proficiency in C++ and experience with AV planning and relevant research are additional qualifications that are highly advantageous.

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What is the salary range for the ML Engineer position at Waymo?

The expected base salary range for the ML Engineer, Foundation Model Evaluation position at Waymo is between $170,000 and $216,000 USD. Actual pay will depend on several job-related factors including experience, skill level, and work location.

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Are there remote work opportunities for the ML Engineer position at Waymo?

Yes, the ML Engineer, Foundation Model Evaluation role at Waymo is remote. However, Waymo may not be able to employ remotely in all locations, so candidates should discuss their preferred remote work location with their recruiter during the interview process.

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Common Interview Questions for ML Engineer, Foundation Model Evaluation
Can you describe your experience with machine learning evaluations?

In your response, highlight specific projects where you have developed methodologies for evaluating ML models. Discuss the tools and frameworks you used, any challenges you faced, and how you overcame them to achieve successful evaluations.

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What deep learning frameworks are you proficient in?

Be prepared to discuss your experience with deep learning frameworks like PyTorch, TensorFlow, or JAX. Provide examples of projects where you utilized these frameworks, focusing on the specific tasks you accomplished and your understanding of their functionalities.

Join Rise to see the full answer
How do you ensure the quality and safety of AI models?

When answering, outline the process you follow to evaluate AI models’ performance. Mention any specific metrics or criteria you consider essential for ensuring safety and reliability, and how you incorporate feedback from testing into improvement cycles.

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Explain a challenging problem you solved in your previous roles?

Choose a specific example that showcases your problem-solving abilities. Detail the problem, the solution you implemented, and the impact of your work on the project. Highlight any innovative approaches you used to address the challenge.

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What strategies do you use for cross-team collaboration?

Discuss how you typically facilitate communication and cooperation between teams. Provide examples of how you’ve collaborated successfully in the past to implement new technologies or approaches in a project.

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Can you share your experience in developing evaluation pipelines?

Describe your role in designing evaluation pipelines in past projects. Talk about the tools you used and the specific evaluations you performed, focusing on how you optimized the pipeline for efficiency and effectiveness.

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What are the latest trends in machine learning you are excited about?

Identify a few upcoming trends or technologies in machine learning that you find particularly interesting. Discuss why they catch your attention and how you think they may impact the field, especially in relation to autonomous driving.

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How do you handle tight deadlines for projects?

Explain your time management strategies, prioritization methods, and any tools you use to ensure you meet deadlines. Share an example where you successfully delivered a project under pressure, focusing on the outcome.

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What motivates you to work in the field of autonomous driving?

In your answer, convey your passion for technology and innovation within the autonomous driving realm. Discuss how this motivates you to tackle complex problems and contribute to advancements in safety and mobility.

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How would you approach testing a new AI model developed by your team?

Describe the steps you would take to create a robust testing strategy for a new AI model. Include considerations for simulation, real-world testing, and methodologies for quality assurance to ensure effective evaluations.

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Waymo’s mission is to make it safe and easy for people and things to move around. With the Waymo Driver, we can improve the world’s mobility while saving thousands of lives.

102 jobs
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BADGES
Badge ChangemakerBadge Diversity ChampionBadge Global CitizenBadge InnovatorBadge Office VibesBadge Work&Life Balance
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Full-time, remote
DATE POSTED
March 28, 2025

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