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Staff Tech Lead, Perception, Pre-training & Distillation

Waymo

Mountain View, California, United States, San Francisco, California, United States

Research Science

$251,000 - $310,000

Posted 15 days ago

manageronsite

Verified open on Sep 16, 2026 · posted 14 days ago

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 Perception team builds the system which learns the spatial-temporal representation and their semantic meanings of the surrounding environment of the self-driving car, i.e., the system that “perceives” the world around the car. We work jointly with downstream teams on the optimization and integration into the Waymo Driver. We conduct our own research to address real-world problems and collaborate with research teams at Alphabet. We have access to millions of miles of driving data from a diverse set of sensors, enabling engineers like you to (1) develop methods for efficiently learning from large scale real-world data, to (2) develop models and model training at scale, to (3) analyze real-world behavior and develop systems for handling the complexities of interacting with the real-world

In this role you will report to a Sr Staff Technical Lead Manager.

You will:

  • Train multi-billion parameter spatio-temporal foundation models on multi-billion frame data sets.
  • Deliver pre-trained models for production usage, ideally for usage in real-time systems.
  • Develop self-supervised learning, including image/video encoder, 3D point cloud encoder, spatio-temporal reconstruction or future prediction, and vision-language contrastive learning.
  • Develop multi-teacher distillation recipes.
  • Develop methods to understand and evaluate the quality of latent representations from pre-training. Collaborate with the post-training team to ensure pre-training delivers the world knowledge representation needed for the multitude of post-training tasks.
  • Develop methods to curate and effectively use diverse datasets in training.
  • Be a key contributor to technical roadmaps.

You have:

  • MS or PhD in Computer Science or a similar discipline, or an equivalent amount of deep learning experience
  • 5+ years experience in Machine Learning and/or Computer Vision
  • Fluent in Python
  • In-depth experience with ML frameworks like PyTorch or JAX

We Prefer:

  • Publications at top-tier conferences like CVPR, ICCV, ECCV, ICLR, ICML, ICRA, RSS, NeurIPS, AAAI, IJCV, PAMI
  • Experience with C++
  • Experience with real-time system design

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$251,000—$310,000 USD
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Career context

This role is classified as Research Science.

$224k - $351k is the middle 50% of disclosed salaries, measured from 272 live Research Science postings on this board. Roughly two thirds of postings disclose nothing, so this describes the ones that do, not the whole market.

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