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.
You will
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Develop and optimize radar-based perception pipelines - preprocessing, detection, clustering, and tracking
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Train, deploy, and monitor radar object detection models for ground handling environments
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Fuse radar data with camera and/or LiDAR for robust multi-modal perception
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Build and maintain radar data collection, labeling, and evaluation pipelines
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Architect a deterministic secondary perception system with radar as a primary modality
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Mentor junior engineers on radar perception best practices
You have
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Bachelor’s or Master’s degree in Computer Science, Robotics, Electrical Engineering, or a related field
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3+ years of focused experience in radar perception (signal processing, clustering, detection, tracking)
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Deep understanding of radar fundamentals - range-Doppler processing, CFAR detection, beamforming, ghost/multipath mitigation
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Experience with automotive or industrial radar sensors (continental, TI, Oculii, or similar)
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Python, C++, and ROS2 proficiency
We Prefer
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PhD in Computer Science, Robotics, Electrical Engineering, or a related discipline
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Experience deploying radar models to production
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Experience developing CUDA kernels
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Experience fusing radar with camera/LiDAR in a production stack
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Familiarity with radar-specific datasets (RADIal, RadarScenes, CARRADA, or similar)