Research Scientist, Map Scalability
Company websitewaymo.com (Waymo, opens in new tab)
Base salary $213K to $263K
Employer-published annual base salary, USD. Advertised base range in Mountain View, CA +2 more
You apply on the employer's own site. Six Figure Work does not handle applications.
- LocationMountain View, CA +2 more
- WorkplaceWorkplace not stated
- Status at last checkSource accepting applications when checked
- Last checked (2 h ago) · observed since
All places named
- Mountain View, CA
- San Francisco, CA
- New York City, NY
About this job
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.
You will:
- Solve fundamental and applied research problems related to world understanding using VLMs, generative modeling and 3D reconstruction at large scale.
- Prototype and iterate on various research ideas using Waymo's internal driving data
- Scale and productionize world understanding solutions in collaboration with engineering teams across Waymo
- Present research findings to a wide audience within Waymo and Alphabet, with the possibility of publishing results to the research community
You have:
- Master’s or PhD degree in Computer Science, Artificial Intelligence, Machine Learning, Deep Learning, or in a similar discipline.
- 1-3+ years of experience in a related field.
- Expert in either Foundational VLMs, Computer Vision or learning-based 3D reconstruction methods (3DGS, NeRF).
- Strong ML software engineering skills in Python/C++ with an ability to rapidly prototype solutions.
- Familiarity with major ML Frameworks (JAX, Tensorflow, Pytorch).
We prefer:
- Publications at top-tier conferences like CVPR/ICCV/ECCV/ICLR/ICML/NeurIPS/IROS/CoRL etc.
- Hands-on experience productionizing and scaling ML solutions beyond the research stage.
- Fundamentals in 3D vision and/or computer graphics.
- Domain experience in the autonomous vehicle or simulation space.
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
$213,000—$263,000 USD
Source: Waymo on Greenhouse · View original posting (opens in new tab)
Pay in context
This role's base floor ($213,000) is above 67% of the 1,503 Data & ML roles in California listed on this site; 14 others list the same floor. Their median floor is $187,000; the middle half runs from $158,941 to $229,900.
Only jobs on this site count, and each one publishes a base salary of $100,000 or more, so this compares six-figure jobs with each other, not with the whole market. Computed Nov 7, 2026.
This listingResearch Scientist, Map Scalability$213K to $263K
Senior Software Engineer, Fleet Response Infrastructure$213K to $263K
Senior Data Scientist, Simulation Capacity Optimization$213K to $263K
Senior Machine Learning Engineer, Vehicle Interaction & Behavior Policy ML$213K to $263K
Senior Machine Learning Engineer, Scenes, Traffic Controls$213K to $263K
Senior Software Engineer, Chassis$213K to $263K
Associate Counsel, Regulatory$213K to $263K
Chart as a table
| Role | Published base |
|---|---|
| Research Scientist, Map Scalability (this listing) | $213K - $263K |
| Senior Software Engineer, Fleet Response Infrastructure | $213K - $263K |
| Senior Data Scientist, Simulation Capacity Optimization | $213K - $263K |
| Senior Machine Learning Engineer, Vehicle Interaction & Behavior Policy ML | $213K - $263K |
| Senior Machine Learning Engineer, Scenes, Traffic Controls | $213K - $263K |
| Senior Software Engineer, Chassis | $213K - $263K |
| Associate Counsel, Regulatory | $213K - $263K |
Observed changes
- First observed on the employer's board
- Began meeting the published-salary criteria
- Observed since
- Employer-stated posting date
- 2026-09-08
Where this pay comes from
Location as the employer wrote it: Mountain View, CA, U.S.A ; San Francisco, CA, U.S.A ; New York City, NY, U.S.A
$213,000—$263,000 USD
- Method
- Employer text, read with fixed rules and re-verified
- Checked
- Rule set
- us-base-v2
The pay passage appears in the employer's own job text. Fixed, deterministic rules located it, and the passage below was checked against the stored copy of the posting.
What we verified
- The pay figures come from the employer's own listing, quoted exactly above.
- The pay is an annual base salary in US dollars with a minimum of at least $100,000.
- The role was publicly listed on the employer's job board when last checked.
We do not verify what the employer will actually offer, whether the employer is still recruiting for the role, or anything beyond what the employer published. Full methodology.
