Job VC

We are looking for a Computer Vision Engineer with a solid foundation in classical computer vision and hands-on experience implementing low-level CV algorithms. The ideal candidate will have exposure to SLAM, Visual-Inertial Odometry (VIO), and sensor fusion, with responsibilities adjusted according to experience level.
Responsibilities:
Implement and optimize low-level computer vision algorithms under guidance
Contribute to modules related to feature extraction, tracking, matching, and geometric processing
Assist in the integration and testing of SLAM/VIO components
Perform experiments, analyze results, and help prepare reports
Work closely with senior engineers to explore and apply recent CV research.
Required Qualifications:
1+ years of hands-on experience with classical computer vision
Basic understanding of geometric computer vision principles
Experience implementing low-level CV algorithms (e.g., filtering, feature detection, camera models)
Familiarity with SLAM or VIO concepts
Working knowledge of C++ and Linux
Ability to learn quickly and navigate recent CV researc
Degree or ongoing studies in a STEM field.
Nice to Have:
Experience with Python
Knowledge of neural networks and CV libraries/frameworks (OpenCV, NumPy, PyTorch, ONNX, Eigen, etc.)
Experience with sensor fusion techniques
Familiarity with embedded or real-time systems