Machine Learning Engineer, Simulation Realism
This role focuses on advancing Waymo’s simulation realism by designing and optimizing machine learning models that interact with high-fidelity virtual environments, bridging the gap between real-world and simulated autonomous driving scenarios. You’ll collaborate with cross-functional teams to improve training efficiency, validate model robustness, and enhance the Waymo Driver’s performance through cutting-edge simulation techniques.
Skills required
About this role
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 Simulator Team at Waymo builds state-of-the-art simulations of realistic environments for testing and training the Waymo Driver. Our team is a diverse and collaborative group of software engineers, machine learning (ML) engineers, and data scientists. We develop industry-leading simulation solutions using advanced ML algorithms that measure and enhance the performance of the Waymo Driver. By applying machine learning, we model the real world, including realistic agents (vehicles, pedestrians, cyclists, motorcyclists), roads, traffic control systems, and weather conditions.
To increase the fidelity and steerability of our simulations, we employ the latest ML technologies such as large foundational World Model trained on our datasets, world understanding and reasoning capabilities for tail cases, and reinforcement learning for long term credit assignment. We also invest in capable infrastructure that allows us to quickly set up and roll out multiple counterfactual scenarios to rigorously test our autonomous driving systems.
In this hybrid role, you will report to a Senior Staff Tech Lead Manager
You will:
- Drive innovation in ultra-realistic world simulation for autonomous vehicles. You will develop the latest simulation technologies using foundation models for embodied agents.
- Apply your deep Machine Learning (ML) expertise, in Generative AI (GenAI), to push the boundaries of simulation realism and directly influence the advancement of autonomous driving technology.
- Work with Waymo's foundational AI research team to transfer research into scalable and production-ready solutions.
You have:
- 5+ years of experience with ML software engineering
- 5+ years of experience with Python
- 5+ years of ML software experience with machine learning framework including Pytorch, Tensorflow, Jax/Flax ,
We prefer:
- Experience working with, creating and/or developing ML models for robotics and/or self driving vehicles
- Strong C++ in production setting, with experience in integrating ML models in production system
- Experience in training large scale models on GPU/TPU clusters are strongly preferred
#LI-Hybrid
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
