Staff Machine Learning Engineer, Waymo

• M.S. or Ph.D. in Computer Science, Machine Learning, AI, or a related technical field (or equivalent practical experience)
• 7+ 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

Desirable

• The DUE ML Core London team will build and operate scalable machine learning and data systems, simulation workflow and insight tools, improve and speed up the evaluation and onboard developer 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 who are passionate about developing machine learning techniques for the Evaluation systems on our autonomous vehicles, and have an incessant drive to improve the performance of our technology stack
• 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