Staff Machine Learning Engineer, Vehicle Compliance Reasoning

Waymo•Mountain View, CA

9h•Hybrid

About The Position

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 are the software engineering team responsible for Waymo's high-level motion planning, encoding Waymo's desired driving behaviors onboard and offboard. Our mission is to build the driving logic needed to deliver a safe, excellent Waymo Driver at scale. We have wide reaching impact into both onboard and off-board system architecture, paving the way for future-looking deep-learning-based explorations. In this team, you'll have an impact on scaling our Waymo Driver's performance and maintaining and improving our excellent safety record as Waymo expands to more cities.

Requirements

PhD, Masters or Bachelors degree in Computer Science, Machine Learning, Robotics, or a related field
7+ years of years of software engineering / machine learning experience
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 dealing with large scale models and datasets
High quality API design with an eye towards eval and data driven technique
Experience with working and solving design problems that cut across multiple components
Proficiency in Python and at least one deep learning frameworks (e.g. PyTorch, JAX, or TensorFlow)

Nice To Haves

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
Eval experience, contributing to scalable eval workflows and building metrics for ML models
Proficiency in C++

Responsibilities

Lead and develop ML solutions for the Waymo driver's decision making and motion planning -- shaping the data, reward, or loss functions in modeling, data mining from large datasets, developing and refining labeling policies.
Analyze, finetune, and evaluate model performance using data-driven approaches
Integrate and deploy ML models on the fleet, conduct end-to-end validation and on-field monitoring.
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
Mentor engineers in leading adoption of ML-based approaches for solving reasoning problems.