Founding Computer Vision Engineer

Overview

• Lead the development and deployment of advanced computer vision algorithms for autonomous UAV systems, focusing on detection, tracking, localization, and navigation.
• Integrate vision systems with ArduPilot-based flight stacks and autonomy frameworks to enhance UAV functionality and performance.
• Optimize computer vision and machine learning pipelines on NVIDIA Jetson platforms for real-time, low-latency execution under resource constraints.
• Collaborate with multidisciplinary teams, including controls, autonomy, firmware, and mechanical engineering, to ensure seamless integration.
• Conduct field testing, debugging, and performance tuning on live UAV systems to ensure reliability and efficiency.
• Document system architecture, experimental results, and deployment workflows to maintain comprehensive project records.
• Participate in hardware integration and flight tests to validate system performance and compliance with regulations.

Key Responsibilities & Duties

• Design and implement computer vision algorithms tailored for UAV applications, including real-time detection and tracking.
• Develop and optimize vision pipelines using OpenCV, CUDA, and embedded Linux platforms for efficient processing.
• Integrate vision outputs with Cube Orange flight controllers and onboard sensors for enhanced UAV autonomy.
• Collaborate with cross-functional teams to align vision systems with overall UAV system architecture.
• Conduct rigorous testing and debugging of vision systems in field and flight environments.
• Document technical workflows, system designs, and experimental findings to support future development.
• Stay updated on UAV regulations and safety practices to ensure compliance and operational integrity.

Job Requirements

• Bachelor of Science degree in a relevant field, with 3+ years of professional experience in computer vision or robotics.
• Proficiency in C++ and Python programming languages, with experience in OpenCV and CUDA frameworks.
• Hands-on experience with ArduPilot and NVIDIA Jetson platforms, including Cube Orange flight controllers.
• Strong understanding of camera models, calibration techniques, and sensor fusion methodologies.
• Experience deploying perception systems on embedded Linux platforms for UAV applications.
• Preferred knowledge of SLAM, visual odometry, VIO, and deep learning frameworks like PyTorch and TensorRT.
• Comfortable with onsite work, hardware integration, and participation in flight tests.