Head of Computer Vision Engineering (m/f/d)
Indexed description
We offer a work environment that is inclusive and open, with a flat hierarchy, and a purpose-driven team. We want to reinforce a culture where great ideas can flourish, and great people collaborate.
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.
- 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
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