Research Scientist, World Modeling

Mountain View, CA, USA

Waymo

Waymo—formerly the Google self-driving car project—makes it safe and easy for people & things to get around with autonomous vehicles. Take a ride now.

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Waymo is an autonomous driving technology company with the mission to be the most trusted driver. Since its start as the Google Self-Driving Car Project in 2009, Waymo has focused on building the Waymo Driver—The World's Most Experienced Driver™—to improve access to mobility while saving thousands of lives now lost to traffic crashes. The Waymo Driver powers Waymo One, a fully autonomous ride-hailing service, and can also be applied to a range of vehicle platforms and product use cases. The Waymo Driver has provided over one million rider-only trips, enabled by its experience autonomously driving tens of millions of miles on public roads and tens of billions in simulation across 13+ U.S. states.

The mission of the Waymo Research team is to develop machine learning solutions addressing open problems in autonomous driving, towards the goal of safely operating Waymo vehicles in dozens of cities and under all driving conditions. As part of our work, we also initiate and foster collaborations with other research teams in Alphabet. Research areas that we are currently focusing on include reinforcement learning, learning from demonstration, generative modeling, Bayesian inference, hierarchical learning, and robust evaluation.

In this hybrid role, you will report to a Staff Research Engineer.

You will:

  • Design and implement generative world modeling solutions to simulate future world states / observations for embodied agents (autonomous vehicles)
  • Develop and maintain scalable data pipelines to process data from multiple sources
  • Design and implement evaluation strategies for generative world models
  • Study and analyze different behaviors of this model, such as scaling efficacy, downstream quality implications, model architecture design ablations, etc.
  • Technical communication to both technical and non-technical audiences regarding research motivations and research findings
  • Conducting cutting-edge research and potentially communicating research findings to the wider academic community via technical reports and/or publications

You have:

  • BS degree in Computer Science or a similar discipline, or an equivalent amount of deep learning experience
  • 1+ years of experience with Deep Learning and Generative Models
  • Familiarity with major ML Frameworks (JAX, Tensorflow, Pytorch)
  • Coding skills, particularly Python

We prefer:

  • PhD degree in Computer Science or a similar discipline, or an equivalent amount of deep learning research experience
  • Publications on top-tier conferences like CVPR/ICCV/ECCV/ICLR/ICML/NeurIPS/IROS/CoRL etc.
  • Substantial involvement in and contributions to high impact industry AI projects
  • Experience in generative models for domains such as world models, images, videos, 3D, human animation, traffic, simulation etc, using techniques such as diffusion or autoregressive models

#LI-Hybrid

The expected base salary range for this full-time position across US locations is listed below. Actual starting pay will be based on job-related factors, including exact work location, experience, relevant training and education, and skill level. Your recruiter can share more about the specific salary range for the role location or, if the role can be performed remote, the specific salary range for your preferred location, during the hiring process. 

Waymo employees are also eligible to participate in Waymo’s discretionary annual bonus program, equity incentive plan, and generous Company benefits program, subject to eligibility requirements. 

Salary Range$158,000—$200,000 USD
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Tags: Architecture Autonomous Driving Autoregressive models Bayesian Computer Science Data pipelines Deep Learning Generative modeling ICLR ICML JAX Machine Learning NeurIPS PhD Pipelines Python PyTorch Reinforcement Learning Research TensorFlow

Perks/benefits: Career development Conferences Equity / stock options Salary bonus

Region: North America
Country: United States

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