Job
- Level
- Erfahren
- Ort
- Wien
- Arbeitsmodell
- Hybrid, Onsite
- Job Feld
- Data, Application
- Anstellung
- Vollzeit
- Vertragsart
- Unbefristetes Dienstverhältnis
- Gehalt
- ab 56.854 € Brutto/Jahr
Job Zusammenfassung
In diesem Job entwickelst du KI-Lösungen für die medizinische Bildanalyse, entwirfst und optimierst Modelle, bereitest Daten vor und führst experimentelle Tests durch, um klinische Anforderungen robust umzusetzen.
Job Technologien
Deine Rolle im Team
- We are looking for a highly skilled and motivated AI Engineer (m/f/d) to develop and deliver innovative AI solutions for healthcare and clinical research.
- In this role, you will design, train and evaluate machine-learning and deep-learning models for medical-image analysis.
- You will build modular and reliable Python components, conduct reproducible experiments and help translate complex clinical and technical requirements into robust AI capabilities.
- Working closely with AI, data, clinical, annotation and software specialists, you will contribute throughout the development lifecycle: from data preparation and model validation to deployment, monitoring and continuous improvement of our shared development tool stack.
- Your responsibilities will include:
- Design, train, evaluate and refine machine-learning and deep-learning models for medical-image segmentation, classification, quantification, forecasting and longitudinal analysis.
- Implement modular, tested and documented Python components for training, inference, evaluation, integration and reporting.
- Prepare and quality-check training and validation data, and support annotation review with clinical and annotation specialists.
- Run structured experiments, select suitable metrics, perform error analysis and document traceable, reproducible results.
- Contribute to shared benchmarks and model-assisted annotation capabilities, support deployment and monitoring under applicable quality and regulatory procedures and contribute to shared development tool stack.
Unsere Erwartungen an dich
Ausbildung
- Bachelor's or Master's degree in a relevant quantitative discipline like computer science, statistics, computer vision, mathematics, biomedical engineering, or equivalent professional experience.
Qualifikationen
- Strong Python skills with PyTorch, Numpy, Pandas, MONAI, etc.
- Sound knowledge of experimental design, model evaluation, robustness, data leakage and reproducibility.
- Strong communication skills in English.
Erfahrung
- At least two years of applied machine-learning or deep-learning experience.
- Practical computer-vision experience, ideally in image segmentation, classification or medical-image analysis.
- Experience with Git, code review, automated testing, Docker and AWS or Azure.
- Healthcare, clinical research, medical-device or model-deployment experience is advantageous.
Unser Angebot
- Room for your own ideas and possibility to grow in your role.
- Friendly and supportive team culture that values diversity.
- Hybrid work model (home office + in-person collaboration).
- Flexible working hours for better work-life balance.
- Well-equipped workplace in a charming office in central Vienna.
- Public transport support.
- Regular team-building events.
- Fully stocked kitchen with snacks and drinks.
- Access to digital mental well-being platform.
- Corporate Benefits and discounts.
- Buddy program to help you get started.
- You can expect a gross yearly salary starting at EUR 56.854,- (on full-time basis, 38.5 hours/week based on the collective agreement) with the willingness to overpay according to your qualification and experience.
Benefits
Work-Life-Integration
Themen mit denen du dich im Job beschäftigst
Job Standorte
Das ist dein Arbeitgeber
RetInSight GmbH
Wien
Wir sind ein innovatives Gesundheitstechnologie-Startup der Medizinischen Universität Wien (Christian Doppler Labor OPTIMA) mit Kunden und Partnern auf der ganzen Welt.
Description
- Gründungsjahr
- 2020
- Unternehmenstyp
- Startup
- Arbeitsmodell
- Hybrid, Onsite
- Branche
- Internet, IT, Telekom, Pharma, Chemie, Biotech, Wissenschaft, Forschung
Arbeitgeber-Reviews
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Gesamt
(1 Bewertung)4.5
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