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At TYTAN, we set a global standard in autonomous air defense with AI-drive, cost-efficient systems that counter unmanned aerial threats at scale. We protect people. We protect critical infrastructure. We protect European sovereignty.
We are now looking for a team member who wants to make an impact. As a Working Student in Data Labeling (m/f/d), you will support the team by preparing and managing perception data, ensuring dataset quality, help organize and collect flight recordings used to train our AI models.
Responsibilities
Annotate and curate perception datasets using our internal annotation tools and help improve it
Maintain and improve the quality of existing labeled datasets
Organize and manage large-scale perception datasets and recording structures (UAV with cameras)
Coordinate with the flight testing team to plan and collect new training data
Assist with organizing recorded flight data and metadata
Your Profile
Currently enrolled in Computer Science, Robotics, Electrical Engineering, or a related technical field
Strong attention to detail and ability to produce high-quality, consistent annotations
Comfortable working with Linux-based systems
Basic experience with Python scripting
Interest in computer vision, machine learning, or robotics
Ability to work independently and take ownership of processes
Good communication skills and ability to coordinate across teams
Nice to Have
Experience with computer vision datasets (e.g. COCO, KITTI, YOLO formats)
Experience using annotation tools (CVAT, Label Studio, Labelme, etc.)
Basic understanding of object detection, tracking, or segmentation models
Experience with Git / DVC
At TYTAN, it is more than just a job; it is about embracing autonomy, personal growth, and purpose. Make a lasting impact in the new era of defense! Join us to create a safer world for all.
TYTAN is an equal-opportunity employer committed to fairness and inclusivity. We do not prioritize any specific religion, gender, nationality, or background. Due to security clearance requirements, affiliations with countries listed under § 13 para. 1 no. 17 SÜG may affect the application process. All qualified applicants are encouraged to apply.
Berlin