I am supporting a very exciting, well-backed AI medical scale up headquartered in Amsterdam, with an additional office in Zurich. The company is on a mission to revolutionize healthcare through large-scale, multimodal AI models that empower clinicians with faster, more accurate decisions.

They are developing the first truly multimodal medical foundation model, trained across diverse medical data types (imaging, text, genomic, clinical), designed to operate at an expert level and serve as an AI assistant for doctors. Their work pushes the boundaries of what existing frontier models can do in medicine, with an emphasis on real clinical impact, scientific rigor, and scalable AI systems.

The Position

As a Machine Learning Engineer / Researcher, you’ll join a world-class, interdisciplinary team of scientists, engineers, and clinicians building the next generation of medical AI models. You’ll have the opportunity to contribute to the research, design, and training of large-scale models that address some of healthcare’s most challenging problems.

You’ll work across the stack of model development, from data curation and pretraining to fine-tuning, evaluation, and deployment. You will help to shape the foundation of a truly transformative AI platform.

Responsibilities

• Research, design, and implement novel machine learning architectures for multimodal medical data (text, imaging, signals, structured data, etc.).

• Build and train large-scale models, from pretraining to domain-specific fine-tuning.

• Develop methods to align model outputs with clinical reasoning and medical safety requirements.

• Collaborate with experts in medicine, ML, and systems engineering to deliver state-of-the-art AI solutions.

• Contribute to scientific publications, open research, or applied model releases where appropriate.

• Optimize models for performance, interpretability, and real-world deployment.

Your profile

• Master’s or PhD in Machine Learning, Computer Science, Engineering, Biomedical AI, Applied Mathematics, or a related field.

• Strong understanding of modern deep learning architectures (Transformers, Diffusion Models, Multimodal Learning, LLMs, etc.).

• Hands-on experience with PyTorch, TensorFlow, or JAX.

• Familiarity with large-scale training pipelines, data preprocessing, and distributed computing.

• A research-driven mindset and curiosity about how AI can advance clinical practice and medical science.

Nice to have:

• Experience with medical data, e.g., radiology, pathology, genomics, or EHRs.

• Contributions to ML research (publications, preprints, open-source projects).

Following your application Joe Templeman, a specialist AI recruiter will discuss the opportunity with you in detail.

He will be more than happy to answer any questions relating to the industry and the potential for your career growth. The conversation can also progress further to discussing other opportunities, which are also available right now or will be imminently becoming available.

This position has been highly popular, and it is likely that it will close prematurely. We recommend applying as soon as possible to avoid disappointment.