We are hiring an experienced Algorithm Engineer to strengthen the core intelligence of unmanned sweeping and washing robots, focusing on coverage planning and cleaning strategies. This role offers exciting careers growth for professionals eager to solve real-world robotics challenges and work on commercial products deployed at scale. You will collaborate closely with navigation and perception teams to optimize algorithms for complex environments such as factories, malls, and offices. These job openings are ideal for candidates seeking long-term employment opportunities in advanced robotics and AI-driven systems.
Requirements include:
1.Education major: Bachelor degree or above in computer science, robotics, automation, artificial intelligence or related majors.
2.Core experience: 2 years or more experience in the development of core algorithms for household sweeping robots or commercial cleaning robots.
3.Technical expertise：
1)Proficient in full-coverage path planning algorithms (such as Boustrophedon, trapezoidal decomposition method, A*, D*, etc.), and have rich practical tuning experience.
2)Proficient in C++ and Python programming, with a solid foundation of algorithms and data structures.
3)Familiar with the Linux development environment and ROS/ROS2 framework.
4Collaboration ability: Possess excellent cross-team communication and collaboration skills, be able to clearly elaborate technical solutions, and promote the integration of different technology stacks (navigation and cleaning).
4.Problem solving: Possess strong hands-on ability and problem analysis ability, and can actively promote the implementation and verification of technical solutions.
5Priority condition (Preferred /Plus):

1)Familiarity with vision-based or laser SLAM, multi-sensor fusion (Laser, V-SLAM, IMU, Wheel-Odom) and autonomous navigation technology stacks is preferred.
2)Experience in dealing with common difficult scenarios of cleaning robots (such as carpet edges, low obstacles, highly reflective floors, and wire entanglement) is preferred.
3)Those who are familiar with kinematics and control theory, and have relevant controller (such as PID, MPC) tuning experience are preferred.

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