Job Opportunities API

The Public Ledger of Openings

← Back to the ledger

Head of Computer Vision Engineering (m/f/d)

Alpine Eagle GmbH
CompanyAlpine Eagle GmbH
CategoryEngineering
LocationKarlsruhe
RemoteOn-site (inferred)
EmploymentNot stated
LevelDirector
SalaryNot stated by the employer
Posted21 May 2025
Last verified10 Aug 2026
SourceEmployer ATS (greenhouse)
Applications are handled by the employer, not by us.Apply on the employer's site →
Description
At Alpine Eagle, we are a team of specialists with backgrounds in defence, aerospace engineering and machine learning, building the first airborne, swarm-based system to provide protection against the rising drone threat. We believe that recent conflicts have shown the malicious and disruptive potential of drones in both civilian and defense scenarios. In addition, we are convinced that the next step in counter-drone is air-to-air. We want to ensure that all governments and institutions that believe in personal freedom and the rule of law have cutting edge solutions to protect against this rising threat. 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.   ✅ What you need to be successful: Ba chelor’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 te chniques   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 prob lem-solving skills and excellent documentation habits   Collaborative mindset with a team-first attitude       At Alpine Eagle, we are committed to diversity and equal opportunity. We welcome applications from all individuals regardless of ethnic origin