Senior Computer Vision Engineer (slam, vio)

Join us to develop SLAM, Visual-Inertial Odometry (VIO), and state estimation solutions for real-world robotics and navigation systems.

We're looking for an engineer with a strong mathematical background and extensive experience in classical and geometric computer vision. You'll independently design, prototype, and optimize computer vision algorithms, quickly turn research ideas into working solutions, and contribute to technical decisions across the development process.

Responsibilities:

• Design, develop, and optimize classical and geometric computer vision algorithms
• Work with feature tracking, matching, and geometric processing
• Develop and improve SLAM / VIO and state estimation pipeline components
• Integrate and test multi-sensor fusion systems (camera + IMU)
• Design and run experiments, evaluate algorithm performance
• Translate research papers into practical implementations
• Collaborate with cross-functional engineering teams

Required Qualifications:

• 5+ years of professional experience in computer vision, robotics, or a related field
• Deep understanding of linear algebra, statistics, and optimization methods
• Strong hands-on experience with classical and geometric computer vision
• Strong understanding of camera models, feature detection and tracking, geometry, and state estimation
• Proven experience developing SLAM, Visual-Inertial Odometry (VIO), or related localization systems
• Strong C++ development skills and experience with Linux
• Experience designing, implementing, and optimizing production-ready computer vision algorithms
• Ability to independently investigate research papers and implement state-of-the-art methods
• Experience working on R&D projects
• Degree in Computer Science, Mathematics, Physics, Engineering, or related 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
• Robotics or navigation background