About the Team The DUE ML Core London team builds and operates scalable machine learning systems, simulation workflows, and insight tools designed to improve the evaluation and developer onboarding journeys. By combining expert human judgment with advanced machine learning models, we deliver training and evaluation data for hundreds of metrics and components that comprise the Waymo Driver. We are looking for researchers and software engineers passionate about developing ML techniques for evaluation systems and driving performance improvements across our technology stack.

You will:

• Build scalable systems for training and fine-tuning large-scale generative models to produce and evaluate realistic driving behaviors.
• Lead the implementation and iteration of novel Reinforcement Learning (RL) algorithms, reward functions, and training paradigms tailored for generating high-fidelity driving behaviors.
• Lead the development of cutting-edge Deep Learning and Generative AI (LLM/VLM) solutions to enhance human-led triaging, automate high-volume workflows, and detect critical anomalies in driving behavior.
• Oversee the production and optimization of ML models used to assess the performance of Waymo's fleet across millions of miles.
• Monitor industry trends and Alphabet-wide research to develop novel Reinforcement Learning from Human Preference (RLHF) based data collection and evaluation systems.
• Partner with Prediction, Planning, and Research teams, as well as senior leadership, to deliver on important strategic efforts.

We'd like you to have:

• M.S. or Ph.D. in Computer Science, Machine Learning, AI, or a related technical field (or equivalent practical experience).
• 5+ years of hands-on experience applying Machine Learning models, with a specific focus on Reinforcement Learning.
• Demonstrated expertise in deep learning, sequence modeling, and generative models.
• A strong publication record or a history of impactful project delivery in RL or related areas.
• Proficiency in Python and standard ML frameworks (e.g., JAX, TensorFlow).
• Experience with large-scale distributed training and data processing.

We prefer you to have:

• 7+ years of relevant experience in ML/RL research and application.
• Experience in autonomous vehicles, robotics, or complex simulation environments.
• Familiarity with state-of-the-art RL techniques, specifically for fine-tuning large models (e.g., RLHF).
• Experience integrating large-scale simulation platforms with ML training workflows.
• A track record of technical leadership and influencing senior stakeholders.