About PARATUS
PARATUS is a fast-growing healthcare software group shaping the future of digital medicine. We build mission-critical solutions that transform radiology and laboratory workflows. With the power of AI, we are taking the next leap: enabling smarter, faster, and safer medical decision-making at scale.
Role Description
As an AI / Machine Learning Engineer (m/f/d), you will be part of a mission: bringing artificial intelligence into clinical practice responsibly. Your work will not end in notebooks or presentations — it will run in real radiology and laboratory environments, where physicians make complex decisions under time pressure.
You will design and train ML and deep-learning models, transform them into production-grade healthcare features, and collaborate closely with clinical and technical experts. Your work will turn data into real-world medical value and help clinicians diagnose patients faster and more accurately.
In short: your work won't save lives by itself — but it will empower those who do.
Your Responsibilities
- Develop, train, optimize, and validate machine-learning and deep-learning models for medical datasets
- Implement production-ready AI features and integrate them into PARATUS Group software solutions
- Build and enhance ML pipelines, including data preparation, evaluation, tuning, deployment, and monitoring
- Create technical documentation for internal teams, audits, and regulatory processes
- Collaborate with clinical users to leverage medical data, annotations, and feedback for model improvement
- Support the transition from research code to scalable, maintainable software components
Must-Have Competencies
- Strong proficiency in Python and modern ML frameworks (e.g. TensorFlow, PyTorch, JAX)
- Deep learning experience (e.g. CNNs, Transformer architectures, multimodal models)
- Proven ability to deliver production-grade AI features — not just prototypes
- Experience in training, tuning, evaluating, testing, and validating models
- Solid understanding of ML pipelines, data handling, overfitting, bias mitigation, robustness, and explainability
- Knowledge of classical machine learning, statistics, and mathematical fundamentals
- Excellent documentation and communication skills
Education & Languages
- Degree in Computer Science, Data Science, Medical Informatics, Mathematics, Physics, Statistics, or a comparable field (BSc required, MSc/PhD preferred)
- Fluent in English (C1), German is a plus
Nice-to-Have Competencies
- Experience in the medical domain (Radiology, Laboratory, DICOM, PACS/RIS/LIS, CT/MRI data)
- Knowledge of C++, C#, Java, or TypeScript for integrating AI components into production software
- Experience with cloud platforms (AWS, Azure, GCP)
- MLOps expertise: CI/CD, MLflow, Weights & Biases, model versioning, monitoring
- Experience with annotation tools, active learning, and labeling pipelines
- Understanding of software regulatory frameworks (MDR, ISO 13485, IEC 62304)
Personal Attributes
- Ownership mindset and a strong results orientation
- Enjoy working in interdisciplinary teams
- Ability to explain complex technical concepts clearly
- High level of responsibility and quality awareness when handling sensitive data