Working Student - Software Engineering (m/f/d)

As a working student in Software Engineering, you support the annotation and quality assurance of training data as well as the structured management of our datasets. You also contribute to the definition and evaluation of KPIs for assessing our models and assist in conducting end-to-end tests of the entire system pipeline. In addition, you research new approaches in the field of computer vision and compare them with existing solutions. Furthermore, you help to further develop our testing infrastructure and evaluation pipelines to ensure continuous quality assurance. What is your Day to Day Mission: • Data Annotation & Dataset Management – Annotate and quality-check training data for object detection and end-to-end planner models, including bounding boxes, segmentation masks, and trajectory labels; maintain and version datasets to ensure consistency and traceability across model iterations • KPI Definition & Model Evaluation – Design, implement, and continuously improve KPIs to monitor and benchmark the performance of ML models deployed on UAVs and UGVs, covering metrics such as detection auracy, latency, precision/recall, and robustness under real-world conditions • End-to-End System Testing – Execute and automate end-to-end integration tests of the full perception and planning pipeline on target hardware (Nvidia Jetson), identifying bottlenecks and regressions across the entire system stack • Research & Model Benchmarking – Independently investigate state-of-the-art publications and open-source models in computer vision, object detection, and autonomous systems; systematically compare novel approaches against our current solutions and document findings in a structured way • Tooling & Test Infrastructure – Contribute to the development of testing scripts, evaluation pipelines, and CI-friendly unit tests to ensure continuous quality assurance of deployed ML components What you bring to the team: • Educational Background – Currently pursuing a degree in Computer Science, Software Engineering, Robotics, or a related technical field • Programming Proficiency – Solid hands-on experience in Python (NumPy, PyTorch/TensorFlow, OpenCV) and working knowledge of C++ for performance-critical or embedded applications • Embedded Systems & Edge Deployment – Familiarity with Nvidia Jetson platforms (e.g. Jetson Orin/Xavier), including experience with deployment workflows such as TensorRT, CUDA optimization, or similar edge inference toolchains • Computer Vision & Machine Learning – Practical experience with ML fundamentals and CV tasks such as object detection, image classification, or semantic segmentation; exposure to model training, fine-tuning, and evaluation workflows • KPI Design & Testing Mindset – Ability to translate high-level system requirements into measurable KPIs and structured unit or integration tests; experience with testing frameworks (e.g. pytest, Google Test) is a plus • Independent & Structured Work Ethic – Self-driven with the ability to manage your own tasks, prioritize effectively, and deliver results with minimal supervision in a fast-paced engineering environment • Communication & Documentation – Strong ability to clearly communicate findings, test results, and research insights to both technical teammates and stakeholders; comfortable writing concise technical documentation and benchmark reports • Research Curiosity & Applied Mindset – Genuine enthusiasm for following the latest developments in autonomous systems, robotics perception, and ML — and the drive to bridge the gap between cutting-edge research and real-world deployment on robotic platforms Why Quantum-Systems: We believe in the power of combined efforts: straightforward tech expertise paired with a customer-centric focus. We are industry pione