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 Planner Reasoning Team builds technology that has an extremely broad impact across the Waymo organization and is the team most directly responsible for the Waymo Driver’s behavior. We have wide reaching impact into both onboard and off-board system architecture, paving the way for future-looking deep-learning-based explorations. The Data-Driven Reasoning team within Planner Reasoning enables new data-driven approaches of Reasoning to improve the Waymo Driver. In this team, your work will include auto-labeling training data, adding Reasoning logic into ML models, data-driven evaluation, data introspection/understanding, and more!

In this hybrid role, you will report to a Technical Lead Manager.

You will:

• Design, develop, and implement ML solutions for autonomous vehicle planning including, but not limited to, modeling, reward/loss shaping, finetuning, reinforcement learning, data shaping, etc.

• Analyze model performance using data-driven techniques to evaluate and compare different approaches

• Stay up-to-date with the latest advancements in autonomous driving and machine learning, and be able quickly prototype, experiment and deploy novel SOTA solutions

• Collaborate closely with partner teams such as perception, research, simulation, and evaluation

You have:

• Experience in applied machine learning including deep learning models, reinforcement learning, feature engineering, loss/reward shaping, data shaping, fine tuning and model evaluation

• Proficiency in Python and at least one deep learning frameworks (e.g. Py Torch, JAX, or Tensor Flow)

• Proficiency in dealing with large scale models and datasets

• Experience in integrating ML models into complicated systems

• PhD, Masters or Bachelors degree in Computer Science, Machine Learning, Robotics, or a related field

We prefer:

• Experience in the autonomous driving domain, including areas like motion planning or perception

• Experience with Large Language Models (LLM) or Vision Language Models (VLM), prompt engineering and chain of thought reasoning

• Experience in applying ML to a robotics problem

• Evaluation experience, contributing to scalable evaluation workflows and building metrics for ML models

• Proficiency in C++

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**$204,000—$259,000 USD**