As a Senior Computer Vision Engineer, you will be responsible for designing, refining, and deploying advanced computer vision algorithms for aerial applications. These algorithms will be integrated onto a variety of robotic platforms, including small drones and full-scale helicopters. You will also provide technical leadership, guiding projects from concept to production, whether through team leadership or by contributing your subject matter expertise.
We seek candidates who are self-motivated, innovative thinkers, passionate about cutting-edge technology. You should be a collaborative team player, an empathetic leader, and a strong communicator. The ideal candidate thrives in a fast-paced environment, can effectively manage multiple tasks, and is enthusiastic about advancing autonomy technology.
Qualifications and Skills
Bachelor's degree in Aerospace Engineering, Robotics, Computer Science, Computer Engineering, or related field.
10+ years of experience in aerospace, robotics, or autonomous flight domains.
Expertise in computer vision or robotic perception.
Hands-on experience with real-time visual-inertial odometry.
Proficiency in IMU calibration.
Experience with sensor configuration and data processing using RGB, IR cameras, lidar, and radar sensors.
Strong C++ programming and design skills.
Experience in GPU development using CUDA.
Experience in software benchmarking, optimization, and multi-threaded development.
Familiarity with software engineering practices and the software development life cycle.
Comfortable working in a Linux environment.
US Citizen or Permanent Resident
Preferred Additional Skills
Master's or Ph.D. in Robotics, Computer Science, or related field.
Experience with ROS or ROS2.
Experience with field testing of robotic systems.
Expertise in designing modular, testable, and extensible C++ APIs.
Familiarity with Python or other programming languages.
Experience with MIPI camera integration.
Experience leading teams or mentoring engineers.
Proven track record of leading technical development within project timelines and budget constraints.