Machine Learning Engineer - Spatial AI

Try&Hire; Paudex; Hybrid; CHF 90,000 - 130,000; Full time

Job summary

Try&Hire in Switzerland seeks a seasoned ML/CV engineer to develop AI models for 2D/3D scene understanding. You will fuse camera data and 3D point clouds into robust semantic representations for indoor environments and support mapping, navigation, and inspection planning.

You will work with Python and PyTorch, build end-to-end pipelines from experimentation to deployment, and analyze real-world drone datasets.

Qualifications

• 3+ years of experience developing machine learning or computer vision systems.
• Deep expertise in semantic segmentation in 2D imagery and/or 3D point clouds.
• Production-grade computer vision systems development.
• Proficiency in Python and PyTorch; strong ML lifecycle understanding.

Responsibilities

• Design and implement AI models for 2D/3D scene understanding.
• Combine camera and point-cloud data into semantic spatial maps.
• Support mapping, navigation and inspection planning with semantic insights.
• Prepare and analyze real-world drone datasets.
• Build Python/PyTorch pipelines from experimentation to deployment.
• Collaborate with mapping, sensors and product teams on spatial AI capabilities.

Skills

Semantic segmentation

Python

PyTorch

ML lifecycle

Production CV systems

English

Job description

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