Senior Staff Machine Learning Engineer, Simulation

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.