About the role
About Sonio Each year, 140M children are born. Birth defects affect 1 in 33 births in developed countries, and in 50% of cases, they are not detected during prenatal examinations. Prenatal medicine is particularly complex, and the scans impose heavy
responsibilities on healthcare professionals. They can also be a source of stress for future parents. Resulting from 5 years of collaboration between world-renowned experts from Necker Hospital and Ecole Polytechnique, Sonio uses artificial intelligence to improve prenatal screening and diagnosis. Based on patented algorithms and a proprietary expert database, Sonio aims to become the reference tool to help practitioners improve screening, reduce diagnostic errors, and optimize pregnant women’s medical path. Sonio's mission is to improve women's and children's health by promoting access and quality of care through technological innovation, medical expertise, and collective intelligence.
About
the role This role is a chance to work on a high-impact, clinically meaningful product: you will contribute directly to the detection of severe fetal anomalies. You will join a cross-functional team and have real influence on what ships and how it performs. You will own the end-to-end delivery of AI components, from data curation and model training to evaluation, error analysis, and iterative improvements in production. You will also join at a pivotal moment in our algorithm development, with the opportunity to take a project from value definition all the way to day-to-day use by clinicians. About the profile Sonio is a mission-driven company — genuine interest in our mission and in meaningful clinical AI applications is essential. We’re looking for someone who is hands-on, curious, and eager to learn fast.
Requirements: 1-2 years of professional experience (including internships) is ideal, but we’re open to strong candidates who feel this role is a good fit. Practical ML experience: you can implement, run, and iterate quickly on AI/ML components (not only design ideas). Experience with medical imaging and/or computer vision is a big plus. Strong Python skills: you follow good practices, write clean code, and are comfortable writing tests. SQL is a plus (or strong willingness to learn). Strong analytical and debugging instincts: you can identify what drives model performance, run solid error analysis, and propose a clear action plan. Clear communication: you can explain technical results, risks, and limitations to non-technical stakeholders (e.g. product, clinicians). Comfortable with ambiguity and autonomy; you take initiative and drive work forward. Master’s degree (minimum) in AI, Computer Vision, Biomedical Engineering (or equivalent proven experience).