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. Driver Refinement and Validation’s (DRV) mission is to build upon the high-quality ML Driver developed by Driver Intelligence, refining its performance to improve autonomous driving in specific, complex real-world contexts and problem areas (e.g., Ride-Hailing contexts). It aims to ensure that the Waymo Driver always computes safe, compliant, comfortable, and useful plans. As an Engineer in DRV, you will bridge the gap between cutting-edge machine learning and real-world vehicle performance, engineering the validation and onboard systems that ensure the autonomous vehicle reliably executes intelligent and predictable maneuvers. You will: Develop next-generation, ML-powered systems that enhance the capabilities of the ML driver and accelerate the rapid scaling of Waymo’s business Fine-tune, adapt, and benchmark state-of-the-art generative models to improve autonomous vehicle perception, motion prediction, and trajectory planning Write high-quality, scalable, and thoroughly tested code to bring cutting-edge ML into production Partner with world-class engineers and product managers to deliver safe and smooth autonomous vehicle behaviors You have: MS in Computer Science, Machine Learning, Robotics, or related technical field, or equivalent practical experience 5+ years of industry experience deploying, evaluating, and maintaining ML-based systems in real-world, production environments Proficient programming skills in Python and/or C++, coupled with strong analytical and debugging abilities Expertise with modern deep learning frameworks, such as JAX or PyTorch We prefer: Experience in deep learning, reinforcement learning, and ML systems Domain expertise in solving prediction, behaviors, motion planning, or related robotics problems ML post-training experience Prior industry experience (e.g. internships) in applied ML or software development Publications in top-tier conferences (e.g., NeurIPS, ICML, ICLR, CVPR, ICCV, ECCV, ICRA, IROS, RSS, CoRL, ACL, or EMNLP) 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 $213,000 — $263,000 USD

Requirements

Must-haves

Develop next-generation, ML-powered systems that enhance the capabilities of the ML driver and accelerate the rapid scaling of Waymo’s business
Fine-tune, adapt, and benchmark state-of-the-art generative models to improve autonomous vehicle perception, motion prediction, and trajectory planning
Write high-quality, scalable, and thoroughly tested code to bring cutting-edge ML into production
Partner with world-class engineers and product managers to deliver safe and smooth autonomous vehicle behaviors
MS in Computer Science, Machine Learning, Robotics, or related technical field, or equivalent practical experience
5+ years of industry experience deploying, evaluating, and maintaining ML-based systems in real-world, production environments
Proficient programming skills in Python and/or C++, coupled with strong analytical and debugging abilities
Expertise with modern deep learning frameworks, such as JAX or PyTorch
Experience in deep learning, reinforcement learning, and ML systems
Domain expertise in solving prediction, behaviors, motion planning, or related robotics problems
ML post-training experience
Prior industry experience (e.g. internships) in applied ML or software development
Publications in top-tier conferences (e.g., NeurIPS, ICML, ICLR, CVPR, ICCV, ECCV, ICRA, IROS, RSS, CoRL, ACL, or EMNLP)

Nice-to-haves

None flagged.

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

mlmachine learningpython

Platform: greenhouse
Effort: quick