Senior/Staff Machine Learning Engineer, Infrastructure

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 DriverTM—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.

Join our ML Infrastructure engineering team advancing state-of-the-art ultra-realistic multi-agent simulations using foundation models.

In this role, you will work at the intersection of ML infrastructure, foundation models, and simulation engineering, with a specific focus on writing high-performance business and simulation logic in JAX/TensorFlow running directly on TPUs to power realistic environments for Reinforcement Learning (RL).

• Design, build, and optimize realistic simulation environments and business logic running on TPUs using JAX and TensorFlow. Implement and optimize large-scale model and data parallelism strategies for training and running foundation models on TPU hardware.
• Collaborate closely with modeling teams to integrate foundation models into simulation pipelines.
• Drive technical architectures and system designs from data engineering through simulation execution to meet business and performance objectives.
• Profile systems, identify performance bottlenecks across ML accelerators, and optimize end-to-end execution speed.
• Translate product and business goals into concrete technical requirements and system deliverables.