Safety Engineer - Risk Management

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 Waymo Safety team works to promote and help to continuously improve the safety of Waymo’s fully autonomous driving technology. Our experts develop safety goals and strategies, and conduct safety engineering analyses to ensure safety is being considered throughout the design and development of our vehicles. The team develops and promotes safety strategies and policies for autonomous vehicles for its work with regulatory authorities, lawmakers, law enforcement and public and non-profit organizations. Our Safety Team also helps advise on compliance with applicable environmental, health, and safety regulations.

In this hybrid role, you will report to Risk Management, Safety Engineer

You will:

You will architect best practices for risk assessment methodologies, including publishing internal guidance on risk model, data sources and computation methods.

You will partner with domain experts from systems, hardware, software, and operations to build robust risk assessments with sustainable overhead for execution and flexibility in the face of an expanding product scope.

You will help define what test coverage and field monitoring is necessary to ensure regression protection.

You will identify stakeholders, learn their pain points, and work to unblock barriers to scale by streamlining rate limiting processes, automating repetitive tasks, and developing tools to enable future projects. You continously evaluate the tools available inside and outside the team/company/industry, using the right ones to unlock increased scale without compromising on rigor.

You will translate complex probabilistic risk models and statistical analyses into clear, actionable safety arguments and executive summaries for technical leaders, cross-functional partners, and safety review boards.

You will champion and promote a robust safety culture and the continuous improvement of the Waymo safety program across the engineering and operations organizations.

You have:

An advanced degree in Computer Science, Robotics, Engineering or other relevant technical field OR 4 years of practical experience involving safety risk assessments and quantitative statistical methods.

Proven experience developing quantitative risk models, Probabilistic Risk Assessments (PRA), or reliability analyses using statistical and mathematical techniques (e.g., Monte Carlo simulations, uncertainty modeling, distribution fitting).

Proficiency in Python, R, or SQL for data manipulation, statistical evaluation, and building automated risk analysis scripts (focusing on data analysis and modeling rather than production software infrastructure).

Strong foundation in the process of risk management, including the end-to-end lifecycle of risk: identification, assessment, mitigation and acceptance of risk (e.g. following ISO 31000/31010 or equivalent standards).

Solid understanding of safety critical system designs and the systems engineering “Verification and Validation” process.

Demonstrated technical project management skills with the ability to effectively manage multiple parallel, cross-functional safety-critical projects and teams. Ability to thrive in ambiguity.

We prefer:

Deep background in data science and statistics with a focus on analyzing large data sets for qua …