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 Planner Evaluation team works on one of the key challenges in autonomous driving: measuring and improving the quality of the software that drives the car. We are looking for experienced data-minded software engineers and data scientists to help us improve how we characterize and evaluate changes to the Onboard software stack (Planner, Perception, etc). If you are passionate about autonomous vehicles and how to use rich, complex data to drive decision making, this is the role for you!
This role follows a hybrid work schedule and reports to an Engineering Manager.
You will:
- Lead and manage a team of software engineers in charge of developing driving quality metrics, measuring the robustness of the Waymo Driver to its input (e.g. sensors data, maps), using a range of techniques including ML, statistics, and algorithms
- Define a long-term strategy, develop roadmaps, and guide the team to execute projects from ambiguous requirements to high-impact deliverables
- Use simulation creatively and mine real world driving logs to measure driving performance
- Champion code health and best practices in a large and complex code base
- Collaborate with other engineers, data scientists, statisticians and the leadership team to deliver evaluation products and help make data driven decisions
You have:
- Master's degree or PhD in Computer Science, Robotics, Statistics, Physics, Math or another quantitative area
- 5+ years of experience in the field of software engineering
- Solid technical leadership in defining vision, strategy and priorities
- Proficiency in C++ or Python in a production environment
- Strong technical communication and collaboration skills
We prefer:
- 2+ years of experience in team management
- Experience coding in C++
- Experience with ML
- Experience with A/B experiment infrastructure
- Exposure to ad-hoc data analysis with SQL
- Experience working in the AV industry
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.
Waymo Mountain View, California, USA Office
1600 Amphitheatre Pkwy, Mountain View, CA, United States, 94043
Waymo San Francisco, California, USA Office
San Francisco, United States
Similar Jobs
What you need to know about the San Francisco Tech Scene
Key Facts About San Francisco Tech
- Number of Tech Workers: 365,500; 13.9% of overall workforce (2024 CompTIA survey)
- Major Tech Employers: Google, Apple, Salesforce, Meta
- Key Industries: Artificial intelligence, cloud computing, fintech, consumer technology, software
- Funding Landscape: $50.5 billion in venture capital funding in 2024 (Pitchbook)
- Notable Investors: Sequoia Capital, Andreessen Horowitz, Bessemer Venture Partners, Greylock Partners, Khosla Ventures, Kleiner Perkins
- Research Centers and Universities: Stanford University; University of California, Berkeley; University of San Francisco; Santa Clara University; Ames Research Center; Center for AI Safety; California Institute for Regenerative Medicine
