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.

Vos tâches

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

Ce que vous apportez

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

Taux d'activité: 100 %
Modèle de travail: Hybride
Option d'engagement fixe après la mission, si les deux parties le souhaitent

Ce qui vous attend

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

Comment postuler

Vous postulez avec votre profil Try&Hire : téléchargez votre CV, vérifiez les informations, indiquez les données clés et votre disponibilité. Une courte vidéo de présentation est facultative, mais elle aide. Notre équipe vous contacte si votre profil correspond à la mission.

Machine Learning Engineer - Spatial AI