Lead the development of machine learning algorithms focusing on perception for autonomous driving, collaborating across teams and mentoring ML developers.

The Software Engineer will develop algorithms and code related to AI, robotics, and sensing technologies, impacting key systems at Zoox.

Develop multimodal large language models for urban driving environments, implement ML solutions, and validate algorithms using real-world data.

Develop advanced Vision-Language-Action models for robotaxis, leading data strategies and improving driving behaviors using machine learning infrastructure.

Contribute to 3D occupancy and segmentation networks development, optimizing deep learning models for real-time inference using multi-modal data fusion.

Design and develop auto-labeling algorithms for autonomous driving, collaborating with ML engineers to enhance data quality and efficiency in model training.

The Machine Learning Engineer Intern at Zoox will work on perception systems, developing algorithms for autonomous driving, collaborating with teams, and leveraging advanced machine learning models and datasets.

Lead data-quality and labeling efforts for perception ML: implement scalable quality measures, drive data-centric model improvements, maintain ontology/class structure, evaluate human vs auto-labeling trade-offs, and build metrics for labeling throughput and annotator/vendor quality.

Lead full-cycle technical recruiting for AI and software roles in Boston. Source, screen, and evaluate candidates, partner with hiring managers and leadership, manage offers, and continuously improve candidate experience and recruiting processes.

Develop multimodal large language models for autonomous vehicles, optimizing performance and safety through advanced machine learning techniques and real-world data validation.

Develop advanced multimodal large language models for autonomous driving, optimize solutions using real-world scenarios, and collaborate with engineering teams.

As a Senior/Staff Software Engineer, you will improve robotic driving behaviors through algorithm development, testing, and performance reviews while ensuring safety and innovation.