Senior Radar Perception Engineer - Autonomy

AeroVect Technologies Inc.; United States; Remote; USD 120,000 - 150,000; Full time

Job summary

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.

You will develop and optimize radar-based perception pipelines, train and deploy detection models, and fuse radar with camera/LiDAR for robust multi-modal perception in production environments.

Qualifications

• Bachelor's or Master's degree in Computer Science, Robotics, Electrical Engineering, or a related field.
• 3+ years of focused experience in radar perception (signal processing, clustering, detection, tracking).
• Deep understanding of radar fundamentals - range-Doppler processing, CFAR detection, beamforming, ghost/multipath mitigation.
• Experience with automotive or industrial radar sensors (Continental, TI, Oculii, or similar).
• Python, C++, and ROS2 proficiency.

Responsibilities

• Develop and optimize radar-based perception pipelines - preprocessing, detection, clustering, and tracking
• Train, deploy, and monitor radar object detection models for ground handling environments
• Fuse radar data with camera and/or LiDAR for robust multi-modal perception
• Build and maintain radar data collection, labeling, and evaluation pipelines
• Architect a deterministic secondary perception system with radar as a primary modality
• Mentor junior engineers on radar perception best practices

Skills

Python

C++

ROS2

Radar perception

Education

Bachelor's/Master's in CS/Robotics/EE

Tools

CUDA

Job description

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.

You will develop and optimize radar-based perception pipelines, train and deploy detection models, and fuse radar with camera/LiDAR for robust multi-modal perception in production environments.