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The Perception Lead will own the perception architecture for Unmannd UAVs, leading development across vision, LiDAR, radar, and sensor fusion pipelines. You will lead the development of high -performance perception systems that integrate seamlessly with autonomy and control. This role requires both deep technical expertise and leadership skills to guide a cross -functional team.
Lead development of UAV perception pipelines for object detection, tracking, mapping, and obstacle avoidance.
Architect and optimize multi -sensor fusion frameworks (e.g., combining cameras, LiDAR, radar, GPS, IMU).
Develop algorithms for SLAM (Simultaneous Localization & Mapping), 3D reconstruction, and terrain awareness.
Ensure perception stack runs in real -time on embedded hardware.
Develop and deploy ML/DL models for vision -based detection, semantic segmentation, and scene understanding.
Implement robust algorithms for adverse environments (low -light, rain, fog, GPS -denied zones).
Optimize for latency, robustness, and power efficiency in embedded systems.
Work with autonomy engineers to feed perception outputs into planning and navigation modules.
Collaborate with controls engineers to enable perception -informed control loops (e.g., obstacle avoidance).
Define perception testing protocols in simulation (Gazebo, AirSim, Isaac Sim) and real -world flight tests.
Analyze UAV flight logs to improve perception performance and robustness.
Stay at the cutting edge of computer vision, robotics perception, and AI for autonomy.
Evaluate and integrate state -of -the -art techniques (e.g., deep learning for perception, graph -SLAM, event -based vision).
Contribute to long -term strategy for making UAV perception certifiable and safety -critical.
Master’s or Ph.D. in Robotics, Computer Vision, Machine Learning, or related field.
6–10 years of experience in perception for robotics, drones, or autonomous vehicles.
Strong expertise in:
Sensor fusion (EKF, UKF, particle filters).
SLAM and mapping frameworks (ORB -SLAM, Cartographer, RTAB -Map, LOAM).
Computer vision & ML/DL (OpenCV, PyTorch/TensorFlow, ROS).
Hands -on experience with embedded systems & GPU acceleration (CUDA, TensorRT, Jetson, etc.).
Experience in C++ and Python for robotics software development.
Track record of deploying perception algorithms on real robots/UAVs.
Ownership of Unmannd’s perception architecture and roadmap.
Direct impact on enabling safe autonomous flight in real -world environments.
Access to UAV hardware, flight testing, and high -performance compute resources.
A startup environment with significant growth opportunities.
Competitive salary, and stock options.
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