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