Hardware Engineering is a diverse, innovative, and collaborative group of electrical, mechanical, reliability, software and vehicle engineers. We design, build, and perfect the products which are the eyes and ears of Waymo's autonomous driving technology, and integrate those products into vehicle platforms. We're seeking curious and talented teammates to keep us moving in the right direction.

In this hybrid role, you will report to a Systems Architect

You will:

• Lead and conduct complex, multi-attribute trade studies to define the architecture of the next-generation Waymo Driver, balancing performance, reliability, cost, and other key factors
• Develop and analyze architectural options for the overall Self-Driving System, with a strong emphasis on safety via robust fallback systems and high reliability
• Collaborate with and drive alignment across diverse engineering teams (Software, Hardware, Sensing, Compute, Safety, Reliability) to make holistic and informed architectural decisions
• Define key system interfaces and behaviors, ensuring a cohesive and well-integrated system design
• Create and present clear and compelling technical recommendations to stakeholders and leadership, justifying architectural choices with data and analysis
• Work closely with systems engineering to decompose architectural decisions into clear requirements for subsystem development. Manage and guide architectural change across current and future SDS generations, ensuring consistency and a clear evolution path

You have:

• A bachelor's degree in Engineering (e.g., EE, ME, CS, Aerospace) or a related technical field
• 5+ years of experience in systems architecture, systems engineering, or complex system design, preferably in autonomous vehicles, aerospace, or robotics
• Proven ability to lead and execute complex technical trade studies involving multiple disciplines and competing objectives
• Strong understanding of system reliability principles and experience designing for high availability in safety-critical applications
• Deep understanding of autonomous system components (Sensing, Compute, Software, Networking)
• Exceptional cross-functional communication and collaboration skills, with the ability to influence without direct authority

We prefer:

• Master's degree or higher in a relevant engineering discipline
• Experience with functional safety (ISO 26262) and SOTIF (ISO 21448)
• Experience with Model-Based Systems Engineering (MBSE) tools and methodologies (e.g., SysML)
• Knowledge of reliability engineering analysis techniques (e.g., FMEA, FTA, Weibull analysis)
• Experience with performance modeling and simulation of complex systems