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.
- Perception System Development
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.
- Algorithm Design & Optimization
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.
- Integration & Testing
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.
- Research & Innovation
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.
Requirements
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.
Benefits
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.
