Safety Engineer

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 models, data sources and computation methods.
• You will collaborate with domain experts to build robust risk assessments with sustainable overhead for execution and flexibility in the face of an expanding product scope.
• You will work with domain experts to define what test coverage is needed to support ongoing risk assessments with regression protection and field monitoring.
• You will connect with stakeholders, learn their pain points, and work to unblock barriers to scale. You will streamline rate limiting processes, automate repetitive tasks, and develop tools to enable future projects.
• You will familiarize yourself with tools available inside and outside the team/company/industry to unlock increased scale without compromising on rigor.
• 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.
• Experience in software engineering for simulation and data evaluation, using Python or other high level language (e.g. SQL, R, C++)
• Direct experience developing risk models, sourcing and validating data, and using findings to make decisions/recommendations.
• 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 or equivalent standards).
• Comprehensive understanding of safety critical system design 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:

• Advanced skills in data science and statistics with a focus on analyzing large data sets for quantitative risk reduction, safety insights, and performance assessment.
• Experience building automated, scalable data pipelines and working in production software environments.
• Experience in the role of “Trainer” of quantitative risk assessment methods for a variety of engineering backgrounds.
• Experience with C++ and Python.
• Success as a safety culture champion, influencing engineering culture, ensuring safety is a first-class citizen in every design discussion.
• Proven leadership experience in working with external partners, contractors, suppliers, and regulatory bodies/auditors.