You 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.
Your tasks
- Design and implement AI models and algorithms for 2D/3D scene understanding
- Combine camera and point-cloud data into consistent semantic spatial maps
- Develop semantic understanding to support mapping, navigation and inspection planning
- Prepare and analyze real-world drone datasets
- Evaluate models using quantitative metrics, visualizations and targeted experiments
- Build Python/PyTorch research and production pipelines from experimentation to deployment
- Collaborate with mapping, sensors and product teams on spatial AI capabilities
What you bring
- 3+ years of experience developing machine learning or computer vision systems
- Deep expertise in semantic segmentation in 2D imagery and/or 3D point clouds
- Proven experience developing production-grade computer vision systems
- Strong proficiency in Python and PyTorch
- Strong understanding of the end-to-end ML lifecycle
- Experience with real-world datasets, evaluation and systematic error analysis
- Proficiency in English; French is a plus
Conditions
- Workload: 100 %
- Work model: Hybrid
- Option of a permanent position after the assignment if both sides want it
What to expect
- 100% workload
- Starting date as soon as possible
- Flexible schedules with option to work remotely up to 2 days per week
- 3-6 months interim, then a permanent position
Technologies
- Python
- PyTorch
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Machine Learning Engineer - Spatial AI in Paudex 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.