Head of Computer Vision Engineering

Head of Computer Vision Engineering

Alpine Eagle

Karlsruhe, Germany

As the Head of Computer Vision Engineering, you will play a pivotal role in advancing Alpine Eagle’s drone technology. You will lead and inspire our computer vision and perception team, shaping the future of our UAV solutions. This is a hands-on leadership role where you will develop and optimize computer vision algorithms, drive perception architecture, and collaborate across teams to deliver next-generation drone capabilities.

How you will make an impact:

• Lead the computer vision strategy and roadmap;
• Define milestones aligned with company goals, establish systematic development processes, and ensure timely delivery of innovative computer vision capabilities;
• Design, implement, and optimize computer vision algorithms for visual navigation;
• Develop real-time object detection and classification, multi-object tracking across frames and scenes, and visual SLAM for outdoor navigation;
• Integrate vision systems with robotic platforms and edge devices;
• Collaborate with cross-functional teams to deploy robust solutions in production environments;
• Design and optimize algorithms and architectures;
• Develop advanced computer vision algorithms for drone applications such as object detection, tracking, segmentation, and scene understanding;
• Evaluate and benchmark models using real-world datasets and simulations;
• Build and develop a high-performing team;
• Lead by example, mentor engineers, and foster a culture of growth, collaboration, and technical excellence;
• Stay at the forefront of technology;
• Continuously research and implement state-of-the-art computer vision techniques, with a focus on aerial and C-UAS applications;
• Champion code quality and documentation;
• Promote best practices through code reviews, maintain high code quality, and ensure clear, consistent documentation.

What you need to be successful:

• Bachelor’s or Master’s degree in Computer Science, Robotics, or a related field; PhD is a plus;
• Strong experience with deep learning frameworks (TensorFlow, PyTorch) and architectures such as CNNs, object detectors, and tracking algorithms;
• Proficiency in object detection models (YOLO, Faster R-CNN, SSD, etc.);
• Solid understanding of visual SLAM, structure-from-motion, and navigation techniques;
• Programming skills in Python and C++ (ROS experience is a plus);
• Familiarity with OpenCV, CUDA, and real-time video processing;
• Proven ability to lead and build high-performing teams in fast-paced, innovative environments;
• Hands-on approach with strong ownership and accountability;
• Systematic problem-solving skills and excellent documentation habits;
• Collaborative mindset with a team-first attitude.