Staff Machine Learning Engineer, Simulation

The Simulator team builds state-of-the-art simulations of realistic environments for the testing and training of the Waymo driver. We use machine learning to model the real world, including realistic agents (vehicles, pedestrians, cyclists, motorcyclists etc.), roads, traffic control systems, and weather. To increase the fidelity and steerability of the simulations, we employ large foundation models, trained on our massive datasets that allow us to quickly setup and rollout multiple scenarios to subject our driver to.

We are planning to set up a team in London UK to work with the teams in MTV and Oxford to build these foundation models out and to integrate them into several evaluation and training products. We are looking for research engineers to work on these exciting problems.

In this hybrid role, you will report to an Engineering Director.

You will:

• Be part of a world class research engineering team to grow the state-of-the-art of ultra realistic AV simulations using foundation models
• Collaborate with teams in Waymo Oxford to use large models to improve sim realism
• Design experiments that push the frontiers of AV simulations
• Develop metrics that measure the realism of simulated worlds
• Train and evaluate large models and integrate them into the simulator and its downstream applications
• Help hire outstanding research engineers from diverse backgrounds
• Be a part of a collaborative research engineering team that takes research ideas and productionizes them

We prefer:

• 5+ years experience in applied Deep Learning
• 5+ years coding and design skills
• Experience solving complex production problems using state-of-the-art ML techniques
• Experience taking research to production
• Expertise in Data Analysis or Data Science

#LI-Hybrid