AI/ML Engineer, Clinical AI
Production ML on real clinical data. Direct access at UKE.
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Tech stack
| Location | Hamburg, Germany |
| Employment Type | Full-Time |
| Reports To | CTO / AI Research Lead |
| Start Date | As soon as possible |
About IDM
IDM gGmbH is a nonprofit health-tech company developing AI-powered products for clinical environments. Our technology is deployed at the University Medical Center Hamburg-Eppendorf (UKE), one of Europe's leading university hospitals, and at additional hospital networks across Germany.
Our flagship products include ORPHEUS, a Clinical NLP platform for medical documentation, and ARGO, an integrated clinical workplace. We work at the intersection of cutting-edge machine learning research and real-world clinical deployment — not prototypes, but production systems used by physicians daily.
The Role
As our Senior AI/ML Engineer, you will own the full machine learning lifecycle for clinical AI models — from research and experimentation through to production deployment and monitoring. You will have direct access to clinical real-world data at UKE Hamburg, a rare opportunity in the ML field.
This role combines hands-on engineering with research leadership. You will shape our research agenda, contribute to clinical studies, publish at top venues, and build a research team — all while ensuring your models make a tangible difference in patient care.
What You Will Do
- Develop and deploy Clinical NLP models: Design, train, and optimize ML models for medical documentation, clinical decision support, and healthcare text analysis using real-world hospital data.
- Own the ML lifecycle: Build and maintain end-to-end pipelines including data preprocessing, model training, evaluation, deployment, and monitoring in production clinical environments.
- Lead research initiatives: Drive clinical AI studies in partnership with university medical centers in our network, contribute to publications, and help secure research funding (e.g., Drittmittel, EU grants).
- Build the research team: Mentor students, supervise research assistants, and help grow the AI research function at IDM.
- Advance MLOps practices: Implement model versioning, automated training pipelines, experiment tracking (MLflow, W&B), and robust deployment workflows.
- Optimize for clinical deployment: Adapt model architectures for latency, scalability, and resource efficiency in real-time clinical scenarios.
- Ensure data quality and compliance: Develop strategies for data preprocessing, anonymization, and harmonization across heterogeneous clinical data (text, imaging, time series, genomics).
What We Are Looking For
Must Have
- 3+ years of hands-on experience in ML/AI, with strong focus on NLP
- Deep proficiency in Python and at least one major ML framework (PyTorch strongly preferred, TensorFlow accepted)
- Experience with the HuggingFace ecosystem (Transformers, Datasets, Tokenizers)
- Solid understanding of modern NLP architectures (Transformer-based models, LLMs, encoder/decoder models)
- Experience with MLOps tools and practices (MLflow, Docker, CI/CD for ML)
- Strong software engineering fundamentals (Git, testing, code review, documentation)
- Ability to work independently and drive projects from conception to deployment
Strong Plus
- Published research at top ML/NLP conferences (NeurIPS, ICML, ACL, EMNLP, NAACL) or medical AI journals
- Experience with clinical/medical data or healthcare AI applications
- German language skills (not required but beneficial for clinical collaboration)
- PhD or Master's in Computer Science, Machine Learning, Computational Linguistics, or related field
Tech Stack
- Core ML: Python, PyTorch, HuggingFace Transformers, scikit-learn, spaCy
- MLOps: MLflow, Weights & Biases, Docker, Kubernetes, GitLab CI
- Infrastructure: PostgreSQL, S3, Helm, Grafana, Prometheus
- Compute: CUDA, GPU clusters (STACKIT Cloud)
What We Offer
- Direct access to clinical real-world data — a unique opportunity in the ML field
- Freedom to shape the research agenda and publish your work
- A mission-driven nonprofit focused on improving healthcare, not maximizing ad revenue
- Small, senior team where your contributions have immediate impact
- Hybrid work model with office in Hamburg-Eppendorf (directly next to UKE)
- Flexible working hours and a supportive, collaborative culture
- Professional development budget and conference attendance
Sounds like you?
Send us your CV and anything else you want to show. We'll get back to you.