Machine Learning Engineer - Prediction and Planning

Zoox is seeking a Machine Learning Engineer to join their Offline Driving Intelligence team, focusing on developing Foundation Models for prediction and planning in autonomous vehicles. This role sits at the intersection of cutting-edge AI and autonomous driving technology, where you'll work on developing novel machine learning pipelines and models to predict other agents' behavior and plan optimal vehicle actions.

The position offers an opportunity to work with state-of-the-art deep learning models, including imitation learning and reinforcement learning techniques, to solve complex autonomous driving challenges in urban environments. You'll be collaborating closely with Perception, Planning, and Simulation teams, contributing to large-scale machine learning infrastructure, and developing crucial metrics for system improvement.

The role requires either a PhD with 1 year of experience or an MSc with 5 years of experience, demonstrating Zoox's commitment to bringing in top talent. The compensation package is competitive, including a base salary range of $204,000 - $245,000, plus Amazon RSUs and Zoox Stock Appreciation Rights. The hybrid work environment in Foster City, CA, offers flexibility while maintaining collaborative opportunities with the team.

This is an excellent opportunity for someone passionate about autonomous vehicles and machine learning to work on real-world applications that will shape the future of transportation. The role combines technical depth in ML with practical applications in autonomous driving, making it an exciting position for those looking to make a significant impact in the field.