Machine Learning Engineer – Medical domain

08 set - Pisa
AIGEA Medical

AIGEA Medical is a MedTech startup. We make women more healthy and happy.

We are looking for a passionate AI Engineer to help build DeepMammo™ , the AI-powered platform for breast cancer screening.

What You’ll Do

- Develop and optimize Machine Learning and Deep Learning models.
- Work with digital images, clinical data, and multimodal AI systems.
- Build AI pipelines using Python, PyTorch, and modern AI frameworks.
- Collaborate with AI researchers, radiologists, and software engineers.
- Support clinical validation and deployment of AI models.

What We’re Looking For

- MSc or PhD in AI, Computer Science, Data Science, Biomedical Engineering, or related fields.

· Machine Learning Engineer / Data Scientist with 5+ years of experience with image processing and computer vision.
- Strong experience with Python and Deep Learning frameworks (PyTorch/TensorFlow).
- Medical imaging experience (DICOM, radiology).
- Experience with cloud technologies, Docker, and Git.
- Good English communication skills.
- Startup mindset, with ability to deal with changing environment.
- Utmost scientific integrity, not afraid to admit uncertainty and mistakes.

Nice to Have





- Vision Transformers, Foundation Models, LLMs, or Generative AI.

· Experience in building products to be commercialised and solve client needs.
- Familiarity with healthcare regulations (MDR, AI Act).

Why Join Us?

- Work on cutting-edge AI for cancer diagnostics.
- Contribute to products with real clinical impact.
- Participate in European research and innovation projects.

Compensation & Benefits

- Salary: €40,000–€44,000 gross annual salary, depending on experience and qualifications.
- Equity Options: opportunity to participate in the company’s growth through an employee equity option plan.

· Working location: hybrid, with working space in our head office in a unique location, a mill in the hills of Pisa, where we meet twice a month.
- Access to cutting-edge AI technologies and healthcare datasets.
- Participation in European research and innovation projects.
- Continuous learning and professional development opportunities.

? Location: Pisa / Hybrid ? Apply: (email hidden)

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