Role Overview
We are looking for a Junior Computer Engineer to work on advanced autonomous navigation capabilities for UAV systems operating in GNSS-denied environments. The role focuses on vision-based navigation, visual odometry, target acquisition, and DSMAC-based guidance.
- You will work closely with GNC, perception, and firmware teams to develop, test, and deploy real-time algorithms that enable reliable navigation without GPS. This is a hands-on role suited for candidates with strong fundamentals in computer vision, embedded systems, and robotics.
Key Responsibilities
- Develop and implement vision-based odometry and localization algorithms
- Support development of GNSS-denied navigation solutions using onboard sensors
- Assist in building target detection and tracking pipelines using camera data
- Contribute to DSMAC (Digital Scene Matching Area Correlation) based navigation systems
- Process and analyze image and sensor data for real-time decision-making
- Work on sensor fusion (camera + IMU) for robust state estimation
- Collaborate with GNC engineers to integrate perception outputs into navigation loops
- Optimize algorithms for real-time performance on embedded hardware
- Support dataset creation, annotation, and validation for vision models
- Participate in SITL/HITL testing and field trials
Required Skills & Qualifications
- 13 years of experience (internships/projects acceptable) in relevant domains
- Strong programming skills in C++ and/or Python
- Fundamentals of computer vision (feature detection, optical flow, SLAM basics)
- Basic understanding of robotics and state estimation
- Familiarity with OpenCV or similar vision libraries
- Understanding of linear algebra, coordinate transforms, and geometry
- Exposure to Linux development environments
- Ability to read and implement research papers or technical specifications
Preferred Qualifications
- Exposure to Visual Odometry / VIO / SLAM frameworks (ORB-SLAM, VINS, etc.)
- Familiarity with ROS/ROS2 ecosystem
- Experience working with camera calibration and image processing pipelines
- Basic understanding of deep learning for vision tasks (object detection, segmentation)
- Exposure to embedded systems or edge AI platforms (NVIDIA Jetson, etc.)
- Understanding of UAV systems or autonomous vehicles
- Academic or project experience in GNSS-denied navigation
