Middle Computer Vision Engineer (slam, vio)

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: 

• Design, implement, and optimize classical CV algorithms independently
• Develop and maintain components of SLAM/VIO pipelines
• Contribute to sensor fusion modules involving visual and inertial data
• Lead experiments, evaluate model performance, and propose improvements
• Review research papers and translate findings into practical solutions
• Collaborate across teams to ensure smooth integration of CV components.

Required Qualifications:

• Strong practical experience with classical CV and geometric vision
• Hands-on experience developing components of SLAM and/or VIO systems
• Proficiency in C++ and confident working in Linux environments
• Solid understanding of multi-sensor systems and data fusion
• Proven ability to prototype, benchmark, and optimize CV algorithms
• Ability to analyze research papers and implement state-of-the-art methods.

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