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.
Hardware Engineering is an 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.
This role follows a hybrid work schedule and you will report to a Systems Engineer.
You will:
- Build unified modeling and simulation tools for vehicle energy consumption and fleet-level Total Cost of Ownership (TCO).
- Develop physics-based simulation models of energy consumption across all vehicle operating modes and environmental conditions.
- Develop a city-level fleet simulator to evaluate interactions across operations models, fleet orchestration, vehicle platform architecture and infrastructure.
- Use these simulation tools to inform critical vehicle/system architecture decisions.
- Collaborate with SW, Product, Data Science and Operations teams, using these models to inform production fleet orchestration software and operations/infrastructure roadmaps.
You have:
- 5+ years of work experience in systems modeling and data science.
- Experience using Python/Matlab/similar programming language to build physics-based models and simulations.
- Experience in data analytics and data-based modeling.
- Strong fundamental education/training in Mechanical Engineering, Electrical Engineering, Physics or a related engineering field.
- Experience leading and delivering cross-functional workstreams/projects.
- Experience communicating complex technical analyses effectively.
We prefer:
- Experience with applying machine learning models in real world applications
- Experience using agentic coding tools like Claude Code, Codex, Antigravity etc.
- Experience in physics-based modeling/simulation of electric vehicle powertrains or other electrical + mechanical + thermal domains.
- Experience applying Operations Research or other optimization approaches to real-world problems.
