Waymo, an industry leader in autonomous driving technology since 2009, is seeking a Principal Software Engineer to lead their Simulator team. This role sits at the intersection of autonomous driving, machine learning, and simulation technology, working on cutting-edge solutions to evaluate and train the Waymo Driver.
The position offers an opportunity to shape the future of autonomous vehicle testing and validation through state-of-the-art simulations. You'll work with a diverse team of ML engineers, software engineers, and data scientists to develop advanced simulation solutions using the latest in machine learning, including large language models, foundational world models, and reconstructive methods.
As a Principal Engineer, you'll drive innovation in simulation technologies, leveraging techniques like 3D Gaussian Splatting and foundational models for sensor data generation. The role involves close collaboration with Waymo's foundational AI research team and ML infrastructure teams to transform research concepts into production-ready solutions.
The position requires strong technical leadership experience, particularly in scaling large-scale ML and data systems. You'll be responsible for the entire lifecycle of product innovations, from initial prototyping to full productization. The role demands expertise in data-driven decision making and the ability to communicate technical strategies effectively to executive stakeholders.
Working at Waymo offers comprehensive benefits including top-tier health insurance, mental wellness support, competitive compensation with equity, and flexible work arrangements. The company culture emphasizes innovation, collaboration, and making a real impact on the future of transportation technology.
This is an exceptional opportunity for a seasoned technical leader who wants to contribute to revolutionizing transportation through autonomous technology. You'll be working with world-class teams, access to extensive resources, and the chance to solve complex technical challenges in simulation and machine learning at scale.