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Full-Stack AI Engineer (Computer Vision & Back-end Focus)

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EMP:Technology
Munich
Tiempo Completo
Remoto
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Descripción

StellDirVor is an independent consulting, trade and technology company specializing in immersive technologies for healthcare.

We support organizations in implementing digital innovations — Virtual, Augmented, and Mixed Reality as well as AI — particularly for learning, training, and real-time assistance in clinical and care environments.

By combining technology and healthcare, we help optimize processes, improve knowledge transfer, and enhance quality of care.

  • Supported by a Germany (ZIM) and Taiwanese (GIPIP) partnership grant, we are currently developing ARAIAS — an AR- and AI-based hands-free training and assistance system for chronic wound care.

Using AR smart glasses, the system enables 3D wound capture, AI-supported analysis, and standardized remote expertise and documentation directly at the point of care.

ARAIAS introduces a new approach to hands-on, safe, and evidence-based learning and training in clinical settings, with the long-term goal of reducing workload for healthcare professionals and improving care outcomes.

We're at an early and exciting stage — moving from concept to working prototype.

The near-term focus is on validating the AI models, establishing the core technical foundations, and building toward a proof of concept we can test in real education and clinical settings.

As the project matures, the work will naturally evolve from experimentation and prototyping into more structured development and productionization.

Notes: Location for this role: Remote (Germany) - due to the nature of the project, we can only consider candidates who are already residing in Germany.

Tasks Design and build AI models for wound analysis — from architecture decisions through evaluation and iteration, with a focus on getting to reliable, clinically meaningful outputs Apply computer vision techniques — object detection, segmentation, depth estimation, or 3D reconstruction — to real medical imaging challenges Handle pre-processing and post-processing of multi-sensor.

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