Senior ML Engineer, Simulation Realism

The Simulator Team at Waymo builds simulations of realistic environments for testing and training the Waymo Driver. Your team will be 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 foundation models trained on our datasets and diffusion technology. We also invest in capable infrastructure that allows us to quickly set up and roll out multiple scenarios to rigorously test our autonomous driving systems.

In this hybrid role, you will report to a Senior Staff Tech Lead Manager

You will:

• Join our world-class research engineering team and 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 in close collaboration with Waymo's foundational AI research team to transfer State-of-The-Art research into scalable and production-ready solutions.

You have:

• 5+ years of experience with ML software engineering
• 5+ years of experience with Python
• ML software experience with machine learning framework including Pytorch, Tensorflow, Jax/Flax ,

We prefer:

• 5+ years of experience including working with creating and developing ML models for robotics and self driving vehicles
• 5+ years of experience with C++ in production setting, with experience integrating ML models in production system
• 5+ years of experience training large-scale models on GPU/TPU clusters are