Quantum Systems
Technology
WorkingStudent-SoftwareEngineering(m/f/d)
Neural analysis suggests this role is
optimal for entry candidates.
“Working Student - Software Engineering (m/f/d) at Quantum Systems. Skills: Software Engineering, Computer Vision, Machine Learning, Data Management. Annotate training data. Quality-check training data”
Industry & Context.
Troubleshooting
What They're Looking For.
Must Have
Degree in Computer Science, Experience in Python, Working knowledge of C++, Familiarity with Nvidia Jetson, Experience with ML fundamentals, Experience with CV tasks, Ability to translate requirements, Experience with testing frameworks
Nice to Have
Experience with pytest, Experience with Google Test
What You'll Do.
Annotate training data
Quality-check training data
Monitor model performance
Benchmark model performance
Execute integration tests
Automate integration tests
Investigate publications
Develop testing scripts
Develop evaluation pipelines
How You'll Work.
Team & Collaboration
Technical teammates
Communication Scope
Communicate findings; Communicate test results; Communicate research insights; Technical documentation
Full Job Description
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 ## Requirements #### What you bring to the team: * Educational Background – Currently pursuing
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