Engineer II

We are seeking a talented Computer Vision Engineer to contribute to our development initiatives in computer vision systems. The ideal candidate will have solid foundational knowledge in Computer Vision algorithms and experience implementing these algorithms in practical applications.

This role involves implementing software solutions, integrating computer vision algorithms, and optimizing performance for real-world UAV applications such as vision-based UAV navigation, object detection/tracking, and obstacle avoidance. You will work with camera data and other sensor inputs including radar, inertial, and GPS data. Experience with multi-modal systems in applications such as Advanced Driver Assistance Systems (ADAS), Robotics, or UAVs is preferred.

Key Requirements & Responsibilities:

Deep Learning and Computer Vision Implementation:

• Implement and integrate DL/CV algorithms into existing system architectures.
• Stay current with developments in computer vision technology and best practices.

Software Development:

• Contribute to software architecture design for computer vision systems.
• Develop modular and maintainable software components that support business objectives.

Hardware Integration:

• Implement solutions that effectively utilize available hardware capabilities.
• Work with hardware teams to ensure optimal software-hardware integration.

Edge Computing Implementation:

• Implement computer vision and deep learning inference solutions for edge devices.
• Optimize algorithms for deployment on resource-constrained devices.
• Address performance requirements for latency and real-time processing.

Team Collaboration:

• Work effectively with cross-functional teams, including hardware engineers, software developers, and researchers.
• Contribute to team communication and project coordination.

Skills & Qualifications:

• 
  Strong foundation in Computer Vision algorithms and Visual SLAM concepts.
• Strong knowledge of 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.