Staff Software Engineer, Vulnerable Road Users

Mountain View, CA

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.

View all jobs at Waymo

Apply now Apply later

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 Perception Vulnerable Road Users (VRU) Understanding team focuses on identifying, understanding, and representing VRU objects (pedestrians, cyclists, motorcyclists) and their interactions with other objects. The team owns VRU perception signals and supports VRU applications across all product areas. Our work improves important product metrics like safety, rider comfort, and cost. We also build the roadmap for VRU signals of onboard systems.

In this hybrid role, you will report to the Technical Lead Manager of VRU Understanding.

You will:

  • Lead modeling efforts for VRU understanding, encompassing nominal, longtail and fine-grained VRU understanding tasks.
  • Leverage onboard and offboard foundation models to streamline the VRU understanding model stack.
  • Bring up the model stack for rapid adaptation to new tasks and data.
  • Establish and maintain a sustainable VRU model stack to facilitate Waymo's multi-platform deployment and scaling goals.

You have:

  • 6+ years of experience in Machine Learning, with a strong focus on computer vision and/or deep learning for perception tasks.
  • Proven experience leading and mentoring a team of engineers or researchers.
  • Deep understanding of state-of-the-art ML techniques for object classification, detection, tracking, pose estimation, and/or action recognition.
  • Proficiency in at least one major deep learning framework (e.g., TensorFlow, PyTorch, JAX).

We prefer:

  • PhD degree in Computer Science or a similar discipline, or an equivalent amount of deep learning experience.
  • Experience with multi-modal perception systems (e.g., combining camera, lidar, radar data).
  • Familiarity with foundation models and techniques for model adaptation (e.g., few-shot learning, transfer learning, domain adaptation).
  • Experience in optimizing ML models for on-device deployment and real-time performance.
  • Background in autonomous driving, robotics, or a related safety-critical domain.
  • Publications in top-tier ML/CV conferences (e.g., NeurIPS, ICML, CVPR, ICCV, ECCV).

#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$238,000—$302,000 USD
Apply now Apply later
Job stats:  1  0  0

Tags: Autonomous Driving Classification Computer Science Computer Vision Deep Learning ICML JAX Lidar Machine Learning ML models NeurIPS PhD PyTorch Radar Robotics TensorFlow

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

Region: North America
Country: United States

More jobs like this