AeroVect is transforming ground handling with autonomy, redefining how airlines and ground service providers around the globe run day-to-day operations. We are a Series A company backed by top-tier venture capital investors in aviation and autonomous driving. Our customers include some of the world’s largest airlines and ground handling providers. For more information, visit www.aerovect.com.
Architect 3D object detection models, including multi-modal approaches (camera, LiDAR, Radar).
Build and maintain data collection and evaluation (metrics) pipeline.
Develop a proprietary multi-modal dataset for training and evaluation.
Train, deploy and monitor 2D/3D object detection models to production.
Experiment SOTA models’ performance.
Mentor junior engineers about best practices.
Master’s or PhD in Computer Science, Robotics, Deep Learning, or a related field.
5+ years of focused experience in architecting and deploying 2D/3D object detection models.
Worked on entire perception stack (sensing, preprocessing, detection & tracking)
Python proficiency
The ability to lead projects autonomously
PhD in Computer Science, Robotics, or a related discipline.
Publications in major conferences like CVPR, ICRA, NeurIPS, IJCAI, AAAI etc