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.
In this hybrid role, you will report to the Sr. Staff Manager.
You will:
- Scale the development of machine learning-based metrics and eval datasets at Waymo with a mixture of strategic and hands-on contributions to solve our toughest evaluation problems
- Address novel evaluation problems by contributing core improvements to our ML models and training regimes.
- Develop and execute a strategy to democratize ML-based development and deployment of metrics and datasets across Waymo by improvements to modeling, mining, training, analysis, and deployment tools.
- Train large, offboard models to generate “ideal” references against which to measure on-vehicle driving.
- Provide technical mentorship, guidance, and thought leadership to other engineers within the team and across collaborating groups.
- Guide and align multiple teams—including Driver Understanding, Simulation, System Engineering, Research, and Onboard Software—on a cohesive evaluation strategy, ensuring cross-functional alignment on goals and priorities.
You have:
- PhD degree in Computer Science, Machine Learning, Artificial Intelligence, or a related technical field, or equivalent practical experience.
- 7+ years of hands-on experience in developing and deploying machine learning applications
- Extensive experience with the practical challenges around building, evaluating, and launching models
- Demonstrated expertise in deep learning, sequence modeling, and generative models.
- Proficiency in Python and standard ML frameworks (e.g., JAX, TensorFlow).
- Proven ability to lead complex and ambiguous technical projects from conception to completion.
We prefer:
- 10+ years of relevant experience in ML research and application.
- Experience scaling and democratizing ML adoption across organizations.
- Experience in the autonomous vehicles domain, robotics, or complex simulation environments.
- Understanding of state-of-the-art RL techniques, including those used for fine-tuning large models (e.g., from human feedback/preferences).
- Experience designing and using metrics for evaluating complex AI systems.
- Track record of technical leadership, influencing senior stakeholders, and driving innovation across team boundaries.
- Excellent communication skills, with the ability to articulate complex technical concepts clearly.