Senior Research Scientist, World Action Modeling

Job Summary

The Waymo AI Foundations team is seeking a researcher to design and implement generative world action modeling solutions to simulate future world states / observations and generate policies for embodied agents (autonomous vehicles).

Responsibilities

• Design and implement generative world action modeling solutions to simulate future world states / observations and generate policies for embodied agents (autonomous vehicles).
• Develop and maintain scalable data pipelines to process data from multiple sources.
• Design and implement evaluation strategies for world action models.
• Study and analyze different behaviors of this model, such as scaling efficacy, downstream quality implications, model architecture design ablations, etc.
• Conducting cutting-edge research and potentially communicating research findings to the wider academic community via technical blog posts, technical reports and/or publications.
• Collaborate inclusively across Waymo/Alphabet to apply developed techniques to Waymo products.

Requirements

• PhD degree in Computer Science or a similar discipline, or an equivalent amount of deep learning research experience, with 5+ years of experience with Deep Learning and Generative Models.
• Strong coding skills in Python and strong familiarity with major ML Frameworks (JAX, Tensorflow, Pytorch).
• Strong familiarity with AI tools in day to day work.
• Experience in large-scale distributed training and different forms of parallelism.
• Experience in generative models for domains such as world models, images, videos, 3D, human animation, traffic, and/or simulation, using techniques such as diffusion and/or autoregressive models.
• Publishations at top-tier conferences like CVPR/ICCV/ECCV/ICLR/ICML/NeurIPS/IROS/CoRL etc.
• Substantial involvement in and contributions to high impact industry AI projects.
• First-hand experience in, and direct contributions to training large world models / world-action models.
• Familiarity with Reinforcement Learning in simulation environments.

Qualifications

• Experience with reinforcement learning in simulation environments.

Skills

• Experience with reinforcement learning in simulation environments.

Benefits

Benefits In accordance with Washington state law, we are highlighting our comprehensive benefits package, which is available to all eligible US based employees. Benefits for this role include: Health, dental, vision, life, disability insuranceRetirement Benefits: 401(k) with company matchPaid Time Off: 20 days of vacation per year, accruing at a rate of 6.15 hours per pay period for the first five years of employmentSick Time: 40 hours/year (statutory, where applicable); 5 days/event (discretionary)Maternity Leave (Short-Term Disability + Baby Bonding): 28-30 weeksBaby Bonding Leave: 18 weeksHolidays: 13 paid days per year