Machine Learning Engineer, Geometry Team at Waymo

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 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. 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 and continuously 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, and (4) optimize models for our onboard and offboard hardware. 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. You will: • 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 You have: • Bachelors 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 Tensorflow. We prefer: • MS or PhD Degree in Machine Learning, Robotics, Computer Science or a similar discipline 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$175,000—$215,000 USD