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EngRadar
EngRadar / AeroVect
Senior Staff Software Engineer, Perception
AeroVect
AeroVect is transforming ground handling with autonomy, redefining how airlines and ground service providers around the globe run day-to-day operations.
AeroVect is the employer — EngRadar is a job radar, not a recruiter. We track this posting from their own careers page and send you straight there; we never handle applications or CVs.
Remote RemoteItalyPolandStockholm Full-time Posted today aviationautonomous-vehiclesrobotics
Apply directly →
Who We Are
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
- 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.
- Build and execute a roadmap for the perception system
- Mentor junior engineers about best practices.
You have
- Master’s or PhD in Computer Science, Robotics, Deep Learning, or a related field.
- 7 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 identify gaps and lead cross functional projects
We Prefer
- PhD in Computer Science, Robotics, or a related discipline
- Full stack AV knowledge
- Experience in architecting perception systems (detection & tracking)
- Publications in major conferences like CVPR, ICRA, NeurIPS, IJCAI, AAAI etc
Posted by AeroVect on their own careers page — you apply directly, no recruiter in between. View original / apply →
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