Job description

Waymo is an autonomous driving technology company with the mission to be the world's 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’s fully autonomous ride-hail service and can also be applied to a range of vehicle platforms and product use cases. The Waymo Driver has provided over ten million rider-only trips, enabled by its experience autonomously driving over 100 million miles on public roads and tens of billions in simulation across 15+ U.S. states. The mission of the Waymo AI Foundations 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. AI Foundations areas that we are currently focusing on include reinforcement learning, learning from demonstration, generative modeling, Bayesian inference, hierarchical learning, and robust evaluation. You will: Solve fundamental and applied research problems related to world understanding using VLMs, generative modeling and 3D reconstruction at large scale. Prototype and iterate on various research ideas using Waymo's internal driving data Scale and productionize world understanding solutions in collaboration with engineering teams across Waymo Present research findings to a wide audience within Waymo and Alphabet, with the possibility of publishing results to the research community You have: Master’s or PhD degree in Computer Science, Artificial Intelligence, Machine Learning, Deep Learning, or in a similar discipline. 1-3+ years of experience in a related field. Expert in either Foundational VLMs, Computer Vision or learning-based 3D reconstruction methods (3DGS, NeRF). Strong ML software engineering skills in Python/C++ with an ability to rapidly prototype solutions. Familiarity with major ML Frameworks (JAX, Tensorflow, Pytorch). We prefer: Publications at top-tier conferences like CVPR/ICCV/ECCV/ICLR/ICML/NeurIPS/IROS/CoRL etc. Hands-on experience productionizing and scaling ML solutions beyond the research stage. Fundamentals in 3D vision and/or computer graphics. Domain experience in the autonomous vehicle or simulation space. 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 $213,000 — $263,000 USD

Requirements

Must-haves

Solve fundamental and applied research problems related to world understanding using VLMs, generative modeling and 3D reconstruction at large scale.
Prototype and iterate on various research ideas using Waymo's internal driving data
Scale and productionize world understanding solutions in collaboration with engineering teams across Waymo
Present research findings to a wide audience within Waymo and Alphabet, with the possibility of publishing results to the research community
Master’s or PhD degree in Computer Science, Artificial Intelligence, Machine Learning, Deep Learning, or in a similar discipline.
1-3+ years of experience in a related field.
Expert in either Foundational VLMs, Computer Vision or learning-based 3D reconstruction methods (3DGS, NeRF).
Strong ML software engineering skills in Python/C++ with an ability to rapidly prototype solutions.
Familiarity with major ML Frameworks (JAX, Tensorflow, Pytorch).
Publications at top-tier conferences like CVPR/ICCV/ECCV/ICLR/ICML/NeurIPS/IROS/CoRL etc.
Hands-on experience productionizing and scaling ML solutions beyond the research stage.
Fundamentals in 3D vision and/or computer graphics.
Domain experience in the autonomous vehicle or simulation space.

Nice-to-haves

None flagged.

Application prep

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Keywords to mirror

aimachine learningmlpython

Platform: greenhouse
Effort: quick

Benefits

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