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In this role, you will develop AI solutions for medical image analysis, design and optimize models, prepare data, and conduct experimental tests to effectively implement clinical requirements.
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Your role in the 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.
- Conduct structured experiments, choose appropriate 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.
Our expectations of you
Education
- Bachelor's or Master's degree in a relevant quantitative discipline like computer science, statistics, computer vision, mathematics, biomedical engineering, or equivalent professional experience.
Qualifications
- Strong Python skills with PyTorch, Numpy, Pandas, MONAI, etc.
- Sound knowledge of experimental design, model evaluation, robustness, data leakage and reproducibility.
- Starke Kommunikationsfähigkeiten in Englisch.
Experience
- 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.
- Experience in healthcare, clinical research, medical devices, or model deployment is advantageous.
What we offer
- 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.
- Voll ausgestattete Küche mit Snacks und Getränken.
- Zugang zu einer digitalen Plattform für psychisches Wohlbefinden.
- Corporate benefits and discounts.
- Buddy program to help you get started.
- You can expect a gross annual salary starting at EUR 56,854 (based on full-time employment, 38.5 hours/week, according to the collective agreement) with a willingness to overpay depending on your qualifications and experience.
Benefits
Work-Life-Integration
Topics you will work on
Job locations
About your employer
Wien
We are a cutting-edge health technology company that was spun off from the Medical University of Vienna. Our software solutions help ophthalmologists and physicians provide precision medicine to their patients, which in turn saves eyesight. We have global customers and partners, making our technology available to people all over the world.
- 2020
- Startup
- Hybrid, Onsite
- Internet, IT, Telecommunication · Pharmaceutical Sector, Chemical Industry, Biotech · Science, Research
Employer reviews
- Team culture
- 4.3
- Engineering
- 4.4
- Career growth
- 4.6
- Working conditions
- 4.8
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