About the Role

We are looking for a highly motivated Autonomous Drone & Swarm Intelligence Engineer to help build the brain of our next-generation UAV systems.

You will work on cutting-edge technologies, from individual drone autonomy to complex multi-agent swarm coordination, deploying real-time AI on the edge.

If you’re passionate about drones, robotics, and intelligent systems, and thrive in a fast-paced environment, we would love to hear from you.

Key Responsibilities

You will work on a combination of these areas depending on your background and our project phase:

1. Autonomous Flight & Navigation

• Design and implement obstacle avoidance and navigation algorithms for UAVs.
• Tune control systems using PID, Kalman filters, and sensor fusion techniques.
• Implement SLAM, visual-inertial odometry (VIO), and GPS-denied navigation pipelines.
• Integrate AI-based modules (e.g., object detection, object tracking, terrain recognition) into onboard navigation systems.
• Simulate missions using Gazebo, AirSim and deploy on real UAVs (e.g., PX4, ArduPilot with Pixhawk or CubePilot).

2. Swarm Intelligence & AI Integration

• Design and implement decentralized algorithms for swarm coordination and collaborative autonomy.
• Implement real-time drone-to-drone communication and decision-making in multi-agent systems.
• Develop and deploy AI algorithms (e.g., multi-agent reinforcement learning, distributed perception) for swarm intelligence.
• Simulate swarm behaviors and validate strategies in tools such as Gazebo or Airsim.
• Deploy swarm systems and AI models to edge devices (e.g., NVIDIA Jetson family) and run tests on real drone fleets.

• Bachelor’s or Master’s in Robotics, Aerospace, Mechatronics, Computer Science, or a related field.
• Passion for drones, autonomous systems, and swarm robotics.
• Proficiency in Python and/or C++.
• Strong background in control theory (e.g., PID, LQR) and sensor fusion (e.g., EKF, UKF).
• Experience with UAV platforms and flight control stacks (e.g., PX4, ArduPilot).

• Experience with SLAM and visual-inertial odometry for UAV applications.
• Experience with multi-agent systems, swarm robotics, or distributed algorithms.
• Experience with ROS/ROS2 and integrating with physical drone platforms.
• Familiarity with machine learning frameworks (PyTorch, TensorFlow).
• Prior work on embedded edge-AI hardware such as NVIDIA Jetson family.
• Contributions to robotics open-source projects or drone competitions.

서류전형 > 1차 면접 > 2차 면접 > 최종합격

• 1차 면접: 코딩 테스트 및 기술 평가(토론 형식)
• 2차 면접: 컬처핏 인터뷰
• 이력서에는 참여한 프로젝트의 역할과 주요 업무를 구체적으로 작성 요망\