Machine Learning Engineer, Geometry Team

Overview

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 lost to traffic crashes.

The Perception team builds the system which learns the spatial-temporal representation and their semantic meanings of the surrounding environment of the autonomously driving vehicle (ADV), 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.

The Geometry team’s mission is to provide an early layer of perception for background subtraction, ground segmentation, and obstacle generation. Projects on our team generally require a diverse skill set of ML and geometric algorithms, onboard sensing and offboard mapping, and the ability to write and maintain efficient robust code. For this role, we are looking for a strong Software Engineer with robotics and machine learning experience, who will help us to accelerate the transition of low-level Perception tasks from algorithms to machine learning.

• Combine ML and geometric algorithms to solve 3D spatial reasoning problems.
• Apply machine learning techniques to build multi-modal sensor fusion architectures and spatial-temporal representation learners for object detection and tracking, occupancy and semantic segmentation, road understanding, etc.
• Develop scalable recipes for large data, large model training running on Alphabet’s compute infrastructure, create methods and recipes for pre-training and post-training.
• Develop methods and recipes for distributed fine-tuning enabling multiple developers to simultaneously improve the model, develop methods and recipes to avoid regression against a production system.
• Develop and maintain model evaluation recipes and metrics for measuring and improving performance of pre-trained and fine-tuned models.

• Bachelor's in Computer Science or a similar discipline, or an equivalent amount of deep learning experience.
• 3+ years experience in Machine Learning and/or Computer Vision.
• Experience with Python and familiarity with C++.
• Experience with ML frameworks like PyTorch, JAX, or Tensor Flow.

• MS or PhD Degree in Machine Learning, Robotics, Computer Science or a similar discipline.

Base salary range for this full-time position across US locations is $175,000—$215,000 USD. Actual starting pay will be based on job-related factors including exact work location, experience, relevant training and education, and skill level. For remote positions, a specific salary range will be provided during the hiring process.

• Health, dental, vision, life, disability insurance.
• Retirement Benefits: 401(k) with company match.
• Paid Time Off: 20 days of vacation per year, accruing at a rate of 6.15 hours per pay period for the first five years of employment.
• Sick Time: 40 hours/year (statutory, where applicable); 5 days/event (discretionary).
• Maternity Leave (Short-Term Disability + Baby Bonding): 28-30 weeks.
• Baby Bonding Leave: 18 weeks.
• Holidays: 13 paid days per year.