Computer Vision R&D Engineer

Quick Facts

• Role: Computer Vision R&D Engineer (UAV navigation, GNSS-denied)

• Work model: Remote

Description

You will work on an innovative R&D project focused on UAV navigation in GNSS-denied environments. The role centers on developing and testing computer vision and Visual-Inertial Navigation algorithms, improving robustness in challenging conditions, and reducing long-flight position drift. You will analyze real UAV flight data and conduct experiments, tests, and benchmarking while documenting results.

Responsibilities

• Develop and test Visual-Inertial Navigation / Visual Odometry algorithms for UAVs

• Improve algorithm robustness to weak lighting, motion blur, vibrations, varying altitude, and low-texture scenes

• Create and run experiments and demanding test scenarios; analyze outcomes statistically

• Work with real flight data (e.g., ROS bags), perform benchmarking, and measure localization performance

• Handle camera–IMU synchronization, sensor calibration, vibration effects, and EKF tuning

• Contribute to methods that limit long-term position error accumulation

• Collaborate with the R&D team and participate in selected test campaign activities

Requirements

• Experience in Computer Vision, Robotics, or State Estimation in R&D projects

• Very good C/C++ and Python knowledge

• Hands-on Linux, Ubuntu, and ROS experience

• Experience with VO/VIO

• Knowledge of feature tracking, loop closure, and visual place recognition

• Practical Kalman Filter/EKF knowledge and sensor fusion using camera, IMU, barometer, and magnetometer

• Experience with ArduPilot EKF3 and interfaces for external navigation data

• Experience optimizing and profiling algorithms on ARM and in real-time environments

• Experience with Raspberry Pi or similar edge devices

• Experience analyzing UAV flight data (e.g., ROS bags)

• Ability to design experiments and test scenarios and analyze results statistically

• Experience with camera–IMU synchronization, sensor calibration, vibrations, and EKF tuning

• Ability to document experiments, methods, parameters, results, and conclusions

• Experience confirmed by publications, a PhD (completed/in progress), or R&D project work

Benefits

• Social package: medical care, group insurance, sports card

• Work with the latest technologies and market trends

• Competitive compensation

• Great working atmosphere