pYou will develop AI-based perception and spatial understanding for inspection drones, combining 2D images and 3D point clouds into robust semantic representations of complex indoor environments. /ph3Your tasks /h3ulliDesign and implement AI models and algorithms for 2D/3D scene understanding /liliCombine camera and point-cloud data into consistent semantic spatial maps /liliDevelop semantic understanding to support mapping, navigation and inspection planning /liliPrepare and analyze real-world drone datasets /liliEvaluate models using quantitative metrics, visualizations and targeted experiments /liliBuild Python/PyTorch research and production pipelines from experimentation to deployment /liliCollaborate with mapping, sensors and product teams on spatial AI capabilities /li /ulh3What you bring /h3ulli3+ years of experience developing machine learning or computer vision systems /liliDeep expertise in semantic segmentation in 2D imagery and/or 3D point clouds /liliProven experience developing production-grade computer vision systems /liliStrong proficiency in Python and PyTorch /liliStrong understanding of the end-to-end ML lifecycle /liliExperience with real-world datasets, evaluation and systematic error analysis /liliProficiency in English; French is a plus /li /ulh3Conditions /h3ulliWorkload: 100 % /liliWork model: Hybrid /liliOption of a permanent position after the assignment if both sides want it /li /ulh3What to expect /h3ulli100% workload /liliStarting date as soon as possible /liliFlexible schedules with option to work remotely up to 2 days per week /lili3-6 months interim, then a permanent position /li /ulh3Technologies /h3ulliPython /liliPyTorch /li /ul #J-18808-Ljbffr
Machine Learning Engineer - Spatial AI Arbeitgeber: Try&Hire
Try&Hire ist ein hervorragender Arbeitgeber, der innovative Technologien im Bereich der KI und Computer Vision fördert. Unsere offene und kollaborative Arbeitskultur ermöglicht es Ihnen, an spannenden Projekten zu arbeiten und Ihre Fähigkeiten kontinuierlich weiterzuentwickeln. Zudem bieten wir flexible Arbeitszeiten und die Möglichkeit, in einem dynamischen Team zu wachsen, das sich leidenschaftlich für wissenschaftliche Fortschritte in der Bildanalyse einsetzt.
