Machine Learning Engineer - Perception Semantics

Zoox's Perception team is at the core of their autonomous vehicle technology, creating world understanding for self-driving robots through sophisticated detection, classification, and tracking systems. As a Machine Learning Engineer in the Semantics and Foundation Model team, you'll be developing advanced multimodal large language models to enhance vehicle environmental understanding.

The role involves developing and fine-tuning models for off-vehicle analysis while optimizing them for real-time performance on their robotaxi platform. You'll work on identifying hazards and interpreting driving restrictions with minimal latency. The position offers the opportunity to work alongside world-class engineers and researchers, utilizing premium sensor data and cutting-edge infrastructure to validate algorithms in real-world conditions.

You'll be responsible for leading the development of multimodal large language models, designing efficient model architectures, and implementing end-to-end ML solutions from research to production. The role requires collaboration with perception, planning, and systems teams to integrate models into the vehicle's decision-making pipeline.

Zoox offers a competitive salary range of $160,000 - $245,000 per year. The company is positioned at the intersection of robotics, machine learning, and design, aiming to revolutionize urban mobility. They value diverse perspectives and encourage applications from candidates who may not meet every listed qualification, recognizing that diversity fosters innovation.

The position is based in Foster City, CA, with a hybrid work arrangement, providing an excellent opportunity to directly impact the safety and capability of Zoox's autonomous system while working with cutting-edge technology in the autonomous vehicle industry.