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

How to apply

You apply with your Try&Hire profile: upload your CV, check the details, enter key facts and availability. A short introduction video is optional but helps. Our team will get in touch if your profile fits the assignment.

Machine Learning Engineer - Spatial AI