Machine Learning Engineer (Simulation Realism, World Model)

Description du poste

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 In this hybrid role, you will report to a Staff Technical Lead Drive innovation in ultra-realistic world simulation for autonomous vehicles by developing and scaling foundation models for embodied agents Design and train multimodal world models and generative architectures using diverse sensory data (such as RGB images, video, and text) Drive closed-loop training and reinforcement learning pipelines to advance simulation realism, policy optimization, and decision-making for autonomous driving Work with Waymo’s foundational AI research team to transfer research into scalable, production-ready solutions Benefits Medical, dental, and vision insurance for employees and dependents Employee assistance programs focused on mental health Personalized workplace adjustments for diverse needs and abilities, including physical, mental, and neurodivergent considerations Access to mental health apps Onsite wellness centers Second medical opinion

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