计算机视觉工程师，空中自主性

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AITAN builds an operational platform for multi-drone missions, unifying drone control, edge AI processing, and mission execution. As a Computer Vision Engineer on the research team, you will drive the perception layer for autonomous aerial systems, running algorithms on the edge in contested airspace. You will take perception from concept and simulation to live flight experiments and production deployment.

• Design and improve vision-based situational awareness systems for aircraft and ground operators
• Build and maintain a shared world model fusing multi-aircraft perception into a coherent 3D representation
• Implement object detection, tracking, and classification pipelines for obstacles, terrain, infrastructure, and other aircraft
• Develop semantic scene understanding for onboard autonomy and offboard mission planning
• Design multi-agent perception architectures that aggregate fleet observations and resolve conflicting views
• Build perception that operates in GNSS-denied and electronic warfare environments
• Combine classical computer vision and modern deep learning for robust low-latency perception
• Own the full algorithm lifecycle from design and simulation to deployment and field tuning
• Collaborate with flight controllers, systems engineers, and operations teams

• Master's degree in Computer Science, Electrical Engineering, Robotics, Aerospace Engineering, or related field
• 4+ years developing computer vision, perception, or autonomy algorithms in production systems
• Strong grasp of classical computer vision and modern deep learning
• Hands-on experience with object detection, SLAM, visual odometry, or 3D scene understanding
• Proven track record taking algorithms from research to real-world operational constraints
• Proficiency in Python and C++ with real-time and latency-constrained deployment
• Experience with modern neural network architectures and deploying trained models in constrained environments

• PhD in a related field
• Experience with drones, aerial systems, or autonomous robotics, ideally in defense or field testing
• Perception systems for GNSS-denied or degraded navigation (visual-inertial odometry, optical flow)
• Multi-sensor fusion, sensor calibration, or sensor-agnostic perception pipelines
• Sim-to-real workflows and field flight test programs
• Deploying models on edge hardware such as NVIDIA Jetson or Qualcomm
• Experience in fast-paced defense tech or deep tech startups