The Simulator Team at Waymo builds state-of-the-art simulations of realistic environments for testing and training the Waymo Driver. Our team is a diverse and collaborative group of software engineers, machine learning (ML) engineers, and data scientists. We develop industry-leading simulation solutions using advanced ML algorithms that measure and enhance the performance of the Waymo Driver. By applying machine learning, we model the real world, including realistic agents (vehicles, pedestrians, cyclists, motorcyclists), roads, traffic control systems, and weather conditions.

To increase the fidelity and steerability of our simulations, we employ the latest ML technologies such as large foundational World Model trained on our datasets, world understanding and reasoning capabilities for tail cases, and reinforcement learning for long term credit assignment. We also invest in capable infrastructure that allows us to quickly set up and roll out multiple counterfactual scenarios to rigorously test our autonomous driving systems.

You will:

• Plan and execute a bold agenda in adapting foundation world models for key simulation needs
• Partner across organizations to land disruptive tech in production
• Incorporate and extend cutting edge research in world modeling/machine learning and robotics to advance the state of the art for world simulation. This may include:
• Data curation, supervised fine-tuning, alignment, reasoning, and controllability 
• Reinforcement learning - Reward, Critic, RL algorithms
• Model scaling, distillation, multi-task learning, representational learning
• Design and drive model quality with metrics first approach  
• Manage and technically lead a team of ML engineers as they grow in their careers

You have:

• Masters degree in Computer Science, Machine Learning, Robotics, similar technical field of study, or equivalent practical experience
• Experience filtering and applying SOTA ML techniques in an applied ML environment and effectively landing impact in production
• Management experience with a team size of 5+.  
• Hands-on experience with an ability to technically lead ICs daily, including knowledge of the codebase, eval and data pipelines, model, and algorithms.
• Proficiency in Python, Numpy, and Jax or Pytorch
• Strong communication and collaboration skills with both research and product teams

We prefer:

• Masters or PhD, preferably in Machine Learning domain
• Proficiency in C++
• Experience in AV planning and applied machine learning
• Experience in working on production validation system and understanding key data techniques/components (ex. Importance sampling, statistics, counterfactuals)