Waymo is an autonomous driving technology company with the mission to be the world's 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’s fully autonomous ride-hail service and can also be applied to a range of vehicle platforms and product use cases. The Waymo Driver has provided over ten million rider-only trips, enabled by its experience autonomously driving over 100 million miles on public roads and tens of billions in simulation across 15+ U.S. states.
The Driver Understanding and Evaluation (DUE) team at Waymo is developing rich metrics for understanding the behavior of the Waymo Driver in the real world, and technologies such as context and scene analysis to understand driving, understanding and augmenting real world driving data to generate rare driving events, build large scale data infrastructure, improve components such as agents and a realistic simulator. These technologies come together to drive the overall technical strategy and methodology used to evaluate the behavior of the Waymo Driver.
The DUE Machine Learning team will build and operate scalable machine learning and data systems, simulation workflow and insight tools, improve and speed up the evaluation and onboard developer journeys. It will combine expert human judgements and advanced machine learning models to deliver training and evaluation data for hundreds of metrics and components that make up the Waymo driver. We are looking for researchers and software engineers who are passionate about developing machine learning techniques for the Evaluation systems on our autonomous vehicles, and have an incessant drive to improve the performance of our technology stack.
You will:
- Lead the design and development of ML infrastructure that takes DUE models from data to training to production serving, including event detection models, triage foundation models, and agents.
- Design and scale distributed systems for large-scale dataset generation, model training, and evaluation across Waymo's real-world and simulation data.
- Own the reliability, efficiency, and observability of production ML serving, including accelerator capacity planning and performance optimization.
- Keep offline evaluation and production inference consistent, so the models we evaluate are the models we serve.
- Drive technical direction for the team, guide architectural decisions, and mentor engineers.
- Collaborate with modeling, evaluation, and platform teams across Waymo to turn product and business goals into measurable technical deliverables.
You have:
- B.S. in Computer Science, Machine Learning, or a related technical field, or equivalent practical experience.
- 7+ years of hands-on experience building machine learning systems.
- Experience designing, scaling, training, deploying, and optimizing large-scale ML systems from data to model.
- Strong coding experience in Python and/or C++.
- Experience with ML frameworks such as JAX, TensorFlow, or PyTorch, including both the user-facing APIs and their internals.
- Proven ability to set technical direction and influence partner teams in ambiguous problem spaces.
We prefer:
- M.S. or Ph.D. in Computer Science or a related field with a specialization in machine learning.
- 10+ years of hands-on experience building production machine learning systems.
- Experience serving ML models in production at scale, including low-latency inference on accelerators (TPU/GPU), SLOs, and safe model rollouts.
- Technical leadership in serving production-quality models, including owning launches, reliability, and on-call for services that other teams depend on.
- Experience with distributed training and accelerator performance profiling.
- Experience in autonomous vehicles, robotics, or large-scale simulation.
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.
Skills Required
- Bachelor’s degree in Computer Science, Machine Learning, or a related technical field, or equivalent practical experience
- 7+ years of hands-on experience building machine learning systems
- Experience designing, scaling, training, deploying, and optimizing large-scale machine learning systems
- Strong coding experience in Python and/or C++
- Experience with JAX, TensorFlow, or PyTorch, including user-facing APIs and internals
- Ability to set technical direction and influence partner teams in ambiguous problem spaces
- Master’s degree or Ph.D. in Computer Science or a related field specializing in machine learning
- 10+ years of hands-on experience building production machine learning systems
- Experience serving machine learning models in production at scale, including low-latency inference on TPU/GPU accelerators, SLOs, and safe model rollouts
- Technical leadership in serving production-quality models, including launches, reliability, and on-call ownership
- Experience with distributed training and accelerator performance profiling
- Experience in autonomous vehicles, robotics, or large-scale simulation
Waymo Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Waymo and has not been reviewed or approved by Waymo.
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Fair & Transparent Compensation — Pay is considered strong for full‑time technical roles, aligning with top‑tier AV/Big Tech benchmarks. Employer materials also emphasize competitive pay with eligibility for bonuses and equity as part of total rewards.
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Healthcare Strength — Coverage spans medical, dental, vision, mental‑health resources, onsite wellness centers, and counseling, with specialized programs such as menopause and transgender medical advocacy. Dependents are included, indicating depth across core health needs.
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Parental & Family Support — Offerings include fertility and family‑forming assistance, parental and baby‑bonding leave, caregiver and elder‑care support, and backup childcare. These programs are positioned to support families through multiple life stages.
Waymo Insights
What We Do
Waymo is an autonomous driving technology company with a mission 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. Waymo reaches out to candidates from official channels only (e.g. directly from @waymo.com email addresses, or through our recruiters or sourcers who are noted as such on LinkedIn). We do not contact candidates about career opportunities through instant messaging apps like Telegram, email addresses from domains other than waymo.com (such as Gmail addresses), direct messages on Twitter, Facebook, and Instagram, or text messages. Visit waymo.com to check out our official job listings.
