Engineer II

Role Overview: You will be a Computer Vision Engineer working on development initiatives in computer vision systems, focusing on implementing software solutions, integrating computer vision algorithms, and optimizing performance for real-world UAV applications like vision-based UAV navigation, object detection/tracking, and obstacle avoidance. Your role will also involve working with camera data and other sensor inputs such as radar, inertial, and GPS data. Experience with multi-modal systems in areas like Advanced Driver Assistance Systems (ADAS), Robotics, or UAVs will be beneficial. Key Responsibilities: - Implement and integrate Deep Learning (DL) and Computer Vision (CV) algorithms into existing system architectures. - Stay updated with the latest developments in computer vision technology and best practices. - Contribute to software architecture design for computer vision systems. - Develop modular and maintainable software components to support business objectives. - Implement solutions that make effective use of available hardware capabilities. - Collaborate with hardware teams to ensure optimal software-hardware integration. - Implement computer vision and deep learning inference solutions for edge devices. - Optimize algorithms for deployment on resource-constrained devices, meeting performance requirements for latency and real-time processing. - Work effectively with cross-functional teams, including hardware engineers, software developers, and researchers. - Contribute to team communication and project coordination. Qualifications Required: - Strong foundation in Computer Vision algorithms and Visual SLAM concepts. - Proficiency in Software Development using C++. - Experience with edge computing and embedded device development. - Familiarity with ROS/ROS2 and hardware acceleration using OpenCL/CUDA is beneficial. - Understanding of software development principles and coding best practices. - Strong problem-solving and analytical skills. - Good communication and teamwork abilities. - Bachelor's degree in Computer Science, Electrical Engineering, or a related field.,