<div>The Perception team at Zoox creates the eyes and ears of our self-driving robots. Navigating safely and efficiently in complex environments requires detecting, classifying, tracking, and understanding various attributes of surrounding objects—all in real-time and with exceptional accuracy.</div><div><br /></div><div>As an engineer in the Scene Understanding team, you will develop advanced ML models that perceive our vehicles surroundings to identify hazards and driving restrictions. You will utilize vision-language models for detecting rare events and ensuring safe driving in these situations. Youll work with state-of-the-art machine learning models that operate in real-time on our robotaxi platform with minimal latency. Collaborating with world-class engineers and researchers across sensors, planning, and other teams, youll have access to premium sensor data and cutting-edge infrastructure to validate your algorithms in real-world conditions.</div><h3>In this role, you will:</h3><ul><li>Design and implement visual scene understanding solutions for robotaxis</li><li>Lead end-to-end data strategy, including mining, auto-labeling, and dataset construction to power our ML flywheel</li><li>Build and utilize vision-language models for rare hazard detection and scene reasoning</li><li>Utilize our large-scale data pipelines and ML infrastructure to research, prototype, and deploy solutions that improve driving behavior</li><li>Partner with cross-functional teams to integrate perception signals</li></ul><h3>Qualifications</h3><ul><li>MS or PhD in Computer Science or related field</li><li>Background in deep learning solutions for vision-language models, large language models, object detection or scene understanding</li><li>Track record of training and deploying state-of-the-art deep learning models</li><li>Hands-on experience with production ML pipelines, including dataset creation, training frameworks, and metrics</li><li>Expertise in Python libraries (PyTorch, NumPy, Pandas)</li></ul><h3>Bonus Qualifications</h3><ul><li>Deep knowledge of cutting-edge computer vision techniques</li><li>Publications in top-tier conferences (CVPR, ICCV, RSS, ICRA)</li><li>Experience with integrating large language models to various tasks</li></ul><div><b>Compensation</b></div><div>There are three major components to compensation for this position: salary, Amazon Restricted Stock Units (RSUs), and Zoox Stock Appreciation Rights. The salary will range from $173,000 to $278,000. A sign-on bonus may be part of a compensation package. Compensation will vary based on geographic location, job-related knowledge, skills, and experience.  </div><div><br /></div><div>Zoox also offers a comprehensive package of benefits including paid time off (e.g. sick leave, vacation, bereavement), unpaid time off, Zoox Stock Appreciation Rights, Amazon RSUs, health insurance, long-term care insurance, long-term and short-term disability insurance, and life insurance.</div><div><br /></div><div><b>About Zoox</b></div><div>Zoox is developing the first ground-up, fully autonomous vehicle fleet and the supporting ecosystem required to bring this technology to market. Sitting at the intersection of robotics, machine learning, and design, Zoox aims to provide the next generation of mobility-as-a-service in urban environments. We’re looking for top talent that shares our passion and wants to be part of a fast-moving and highly execution-oriented team.</div><div><br /></div><div><a href="https://www.linkedin.com/company/zoox-inc">Follow us on LinkedIn</a></div><div><br /></div><div><b>Accommodations</b></div><div>If you need an accommodation to participate in the application or interview process please reach out to accommodations@zoox.com or your assigned recruiter.</div><div><br /></div><div><i><b>A Final Note:</b></i></div><div><i>You do not need to match every listed expectation to apply for this position. Here at Zoox, we know that diverse perspectives foster the innovation we need to be successful, and we are committed to building a team that encompasses a variety of backgrounds, experiences, and skills.</i></div>