Senior Software Engineer, Eval Efficiency & Optimization
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 +3 more
You apply on the employer's own site. Six Figure Work does not handle applications.
- LocationMountain View, CA +3 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, NY
- Pittsburgh, PA
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.
As a Software Engineer, you will solve ill-defined problems at the intersection of statistics, machine learning, and scalable systems engineering. You will develop creative quantitative models to address eval challenges, while providing rigorous mathematical and experimental proof of the correctness and statistical efficiency of your solutions.
You will:
- Tackle ill-defined, ambiguous problems and reduce complex systems into tractable quantitative models.
- Develop statistical techniques that enable our evaluation pipelines to deliver better signals with fewer resources.
- Design and build automation to enhance the efficiency and scalability of our evaluation infrastructure.
- Collaborate with other engineers, data scientists, product managers, and the leadership team to deliver evaluation products and help make data driven decisions.
- Champion code health and best practices in a large and complex code base.
You have:
- BS in Math, Physics, or another quantitative field
- Fluency in implementing statistical, ML, and general mathematical algorithms for large datasets
- Experience adapting techniques in research papers to applied problems
- Strong self-motivation and comfort with ambiguity to navigate complex systems and pursue open-ended problems to completion
- 3-5 years of experience with
- Navigating and modifying a large code base containing a variety of languages, such as C++, Python, and SQL
- Performing statistical analyses
- Building data processing pipelines
- Writing, reviewing, and merging code following industry standards for code health and maintainability
We prefer:
- PhD in a quantitative field
- Experience programming in C++ and Python
- Experience developing, evaluating, and deploying products at scale
- Experience with Agentic AI
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 77% of the 4,294 Software Engineering roles in California listed on this site; 29 others list the same floor. Their median floor is $176,000; the middle half runs from $149,100 to $201,900.
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 listingSenior Software Engineer, Eval Efficiency & Optimization$213K to $263K
Senior Software Engineer, Fleet Response Infrastructure$213K to $263K
Research Scientist, World Model Post-Training$213K to $263K
Senior Data Scientist, Simulation Capacity Optimization$213K to $263K
Senior Machine Learning Engineer, Vehicle Interaction & Behavior Policy ML$213K to $263K
Research Scientist, Map Scalability$213K to $263K
Senior Machine Learning Engineer, Scenes, Traffic Controls$213K to $263K
Chart as a table
| Role | Published base |
|---|---|
| Senior Software Engineer, Eval Efficiency & Optimization (this listing) | $213K - $263K |
| Senior Software Engineer, Fleet Response Infrastructure | $213K - $263K |
| Research Scientist, World Model Post-Training | $213K - $263K |
| Senior Data Scientist, Simulation Capacity Optimization | $213K - $263K |
| Senior Machine Learning Engineer, Vehicle Interaction & Behavior Policy ML | $213K - $263K |
| Research Scientist, Map Scalability | $213K - $263K |
| Senior Machine Learning Engineer, Scenes, Traffic Controls | $213K - $263K |
Observed changes
- First observed on the employer's board
- Began meeting the published-salary criteria
- Observed since
- Employer-stated posting date
- 2026-10-02
Where this pay comes from
Location as the employer wrote it: Mountain View, CA, USA; San Francisco, CA, USA; New York, NY, USA; Pittsburgh, PA, USA
$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.