Lead - Perception (UAVs)

About the Role<\/span><\/b><\/div><\/div>
The Perception Lead<\/b> will own the perception architecture<\/b> for Unmannd UAVs, leading development across vision, LiDAR, radar, and sensor fusion pipelines<\/b>. You will lead the development of high\-performance perception systems that integrate seamlessly with autonomy and control. This role requires both deep technical expertise<\/b> and leadership skills<\/b> to guide a cross\-functional team.
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Key Responsibilities<\/span><\/b><\/div>
Perception System Development<\/span><\/b><\/span>
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Lead development of UAV perception pipelines for object detection, tracking, mapping, and obstacle avoidance<\/b>.
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Architect and optimize multi\-sensor fusion<\/b> frameworks (e.g., combining cameras, LiDAR, radar, GPS, IMU).
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Develop algorithms for SLAM (Simultaneous Localization & Mapping)<\/b>, 3D reconstruction<\/b>, and terrain awareness<\/b>.
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Ensure perception stack runs in real\-time on embedded hardware<\/b>.
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Algorithm Design & Optimization<\/span><\/b>
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Develop and deploy ML/DL models for vision\-based detection, semantic segmentation, and scene understanding<\/b>.
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Implement robust algorithms for adverse environments<\/b> (low\-light, rain, fog, GPS\-denied zones).
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Optimize for latency, robustness, and power efficiency<\/b> in embedded systems.
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Integration & Testing<\/span><\/b>
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Work with autonomy engineers to feed perception outputs into planning and navigation<\/b> modules.
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Collaborate with controls engineers to enable perception\-informed control loops (e.g., obstacle avoidance).
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Define perception testing protocols in simulation (Gazebo, AirSim, Isaac Sim)<\/b> and real\-world flight tests<\/b>.
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Analyze UAV flight logs to improve perception performance and robustness.
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Research & Innovation<\/span><\/b>
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Stay at the cutting edge of computer vision, robotics perception, and AI for autonomy<\/b>.
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Evaluate and integrate state\-of\-the\-art techniques (e.g., deep learning for perception, graph\-SLAM, event\-based vision).
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Contribute to long\-term strategy for making UAV perception certifiable and safety\-critical<\/b>.
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Requirements<\/h3>
Qualifications<\/span><\/b><\/div>
Master\u2019s or Ph.D. in Robotics, Computer Vision, Machine Learning, or related field<\/b>.
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6\u201310 years<\/b> of experience in perception for robotics, drones, or autonomous vehicles.
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Strong expertise in:
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Sensor fusion<\/b> (EKF, UKF, particle filters).
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SLAM and mapping frameworks<\/b> (ORB\-SLAM, Cartographer, RTAB\-Map, LOAM).
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Computer vision & ML/DL<\/b> (OpenCV, PyTorch/TensorFlow, ROS).
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Hands\-on experience with embedded systems & GPU acceleration (CUDA, TensorRT, Jetson, etc.)<\/b>.
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Experience in C++ and Python<\/b> for robotics software development.
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Track record of deploying perception algorithms on real robots/UAVs.
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Benefits<\/h3>
What We Offer<\/span><\/b><\/div>
Ownership of Unmannd\u2019s perception architecture<\/b> and roadmap.
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Direct impact on enabling safe autonomous flight<\/b> in real\-world environments.
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Access to UAV hardware, flight testing, and high\-performance compute resources.
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A startup environment with significant growth opportunities.
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Competitive salary, and stock options.
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