Senior SLAM/VIO Computer Vision Engineer

Job DescriptionCompany Description

Cyberbee is a dynamic startup headquartered in Rosh HaAyin, specializing in low-compute, easy-to-deploy, GNSS-free, SLAM-based navigation systems. Our technology facilitates precise mapping and localization in GPS-denied environments, thereby enabling real-world indoor and outdoor navigation applications.

We are actively seeking a Senior Computer Vision Engineer for the direct development of real-time localization algorithms. This full-time, on-site position emphasizes the delivery of production-ready systems, including:

• Develop and optimize C++ and Python algorithms for real-time localization (e.g., VIO, VO, SLAM)
• Integrate and manage vision and inertial sensor pipelines to estimate pose accurately
• Tune performance, handle threading, memory, and latency on embedded/ARM platforms
• Deploy on hardware, profile, debug, and iterate to ensure stability in real-world scenarios
• Maintain continuous synchronization with the latest literature and methodologies in the domain.
• Mentor team members, participate in code reviews, paired programming, and guide technical development

• Bachelor’s in Computer Science, Software Engineering, or related field
• M.Sc. or Ph.D. is a plus

• C++ and Python Expertise: 5+ years of experience developing performance-critical systems using modern C++ standards and Python.
• Real-Time Localization: 2+ years hands-on experience with real-time localization technologies such as visual-inertial odometry, visual odometry, or SLAM.
• Computer Vision Fundamentals: Solid understanding of computer vision principles, including feature detection, matching, and mapping (deep expertise in bundle adjustment or graph optimization - bonus).
• DevOps Tools: Proven experience with Docker for containerization and CI/CD pipeline implementation - bonus.

• Proficient in embedded or ARM platform development for real-time systems.
• Demonstrated familiarity with Kalman filters or graph-based estimation (bundle adjustment is an advantage).
• Experienced in utilizing the ROS2 framework for drone and/or robotics applications.
• Possesses a background in deep learning frameworks (e.g., PyTorch, TensorFlow).

• Exceptional problem-solving and analytical skills.
• Excellent communication and collaboration within small, agile teams.
• Enthusiastic and dedicated to mentoring and developing peers.
• Proactive, adaptable, and thrives in a fast-paced startup environment.

• Develop and implement production-ready localization systems for GNSS-denied environments.
• Engage daily with real-world data and hardware, and work closely with the edge application
• Participate in an agile, mission-focused team with accelerated deployment cycles.
• Located in Rosh HaAyin, close to the train station

Visit us at cyberbee.ai