Waymo
ML Engineer, Perception Foundation Model
Waymo, Mountain View, California, us, 94039
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 Applied 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.This hybrid role will report to a Perception Research Manager.You will:
Lead the effort of model-platform co-optimization for Waymo's perception foundation model.Dive deep into training and inference efficiency on various platforms such as TPU, GPU, and CPU.Collaborate with other teams, such as perception, simulation, and ML infrastructure, to drive the model optimization.Be curious, innovative, and productive.You have:
Hands-on experience with designing or optimizing neural networks using Transformers and ConvNets.Experience optimizing model efficiency for either large-scale training or inference.Able to learn new models and new frameworks.Track record of optimizing ML models.We prefer:
Experience on low-level optimizations, on CPU/GPU/TPU.Experience on designing, evaluating, or optimizing Transformers.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 remotely, 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:
$192,000 — $243,000 USD
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Lead the effort of model-platform co-optimization for Waymo's perception foundation model.Dive deep into training and inference efficiency on various platforms such as TPU, GPU, and CPU.Collaborate with other teams, such as perception, simulation, and ML infrastructure, to drive the model optimization.Be curious, innovative, and productive.You have:
Hands-on experience with designing or optimizing neural networks using Transformers and ConvNets.Experience optimizing model efficiency for either large-scale training or inference.Able to learn new models and new frameworks.Track record of optimizing ML models.We prefer:
Experience on low-level optimizations, on CPU/GPU/TPU.Experience on designing, evaluating, or optimizing Transformers.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 remotely, 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:
$192,000 — $243,000 USD
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