Waymo Verified

Autonomous Vehicles, Artificial Intelligence, Robotics, Automotive

Research Scientist, RL for Autonomous Planning & World Modeling

Mountain View, CAHybridFull Time$204,000–$259,000 /yrPosted 2 months agoVisa sponsorship available

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Required skills

Reinforcement Learning
Foundation Models
Autonomous Driving
Machine Learning
Robotics
Data parallel
FSDP
sharding

Nice to have

NeurIPS
ICLR
CVPR
ArXiv
technical blog posts
open-source contributions

Role summary

Waymo's AI Foundations team is seeking a Research Scientist specializing in Reinforcement Learning (RL) for Autonomous Planning and World Modeling. This hybrid role involves developing cutting-edge ML solutions for autonomous driving, integrating external research, and collaborating across teams. The ideal candidate will have a PhD or Masters in a relevant technical field with 3+ years of experience in RL or Foundation Models, a strong publication record, and proficiency in distributed training infrastructure. Preferred qualifications include a PhD with a focus on RL or Foundation Models, experience with RL infrastructure, and large-scale training techniques.

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 mission of the Waymo AI Foundations 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. AI Foundations areas that we are currently focusing on include reinforcement learning, learning from demonstration, generative modeling, Bayesian inference, hierarchical learning, and robust evaluation.

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

You will:

Participate in Waymo’s Foundation World Model post-training and evaluation

Research and develop cutting edge RL and Distillation techniques for Autonomous Vehicle Trajectory Planning

Integrate emerging research from the broader AI community into Waymo’s internal RL infrastructure, conducting rigorous ablations to identify and scale the most promising methods

Partner with engineering and research teams across Waymo to share recipes, techniques, and post-training best practices to accelerate our collective know-how

You have:

PhD or Masters in Computer Science, Machine Learning, Robotics, or a similar technical field; with 3+ years of industry or post-doc research experience in Reinforcement Learning or Foundation Models

Demonstration of original contributions to the field through high-impact publications (ArXiv, peer-reviewed conferences like NeurIPS/ICLR/CVPR), technical blog posts, or significant open-source contributions

Proficiency in implementing model training flows in a scalable, distributed and performant manner such as Data parallel, FSDP and other sharding approaches

A willingness to work with complexity of globally distributed inference infrastructure

We prefer:

PhD in Computer Science, Machine Learning, or Robotics, with a research focus on Reinforcement Learning, Foundation Models, or Multi-Modal learning

Extensive experience designing and deploying Reinforcement Learning infrastructure, specifically for on-policy learning or alignment with human preferences

A consistent history of original contributions to the AI community, evidenced by first-author publications at top-tier venues (e.g., NeurIPS, ICLR, ICRA) or maintaining significant open-source ML projects

Experience with large scale (many-machine) training infrastructure and techniques for inference with large models such as model sharding/tensor-parallel

In accordance with Washington state law, we are highlighting our comprehensive benefits package, which is available to all eligible US based employees. Benefits for this role include:

Health, dental, vision, life, disability insurance

Retirement Benefits: 401(k) with company match

Paid Time Off: 20 days of vacation per year, accruing at a rate of 6.15 hours per pay period for the first five years of employment

Sick Time: 40 hours/year (statutory, where applicable); 5 days/event (discretionary)

Maternity Leave (Short-Term Disability + Baby Bonding): 28-30 weeks

Baby Bonding Leave: 18 weeks

Holidays: 13 paid days per year

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$204,000—$259,000 USD

Sample Waymo interview questions

1
Design a data ingestion system
system designmedium
2
Design a simulation-based regression detection system for code changes
system designhard
3
Longest Substring with Two Distinct Characters Find the longest substring with at most two distinct characters. Input: s = "ccaabbb" Output: 5 Explanation: The substring "aabbb" contains exactly two distinct characters and has a maximum length of 5.
codingmedium
4
Alien Dictionary Order Derive the alien dictionary order from a sorted list of alien words. Input: words = ["z","x","z"] Output: "" (Empty String) Explanation: The letter 'z' cannot come before 'x' and then suddenly after 'x', creating a cycle and making the dictionary invalid.
codingmedium
5
Palindrome After Deleting One Character Determine if a string can be a palindrome after deleting at most one character. Input: s = "abc" Output: FALSE Explanation: Deleting any single character leaves either "ab", "bc", or "ac", none of which result in a valid palindrome.
codingmedium

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