Chaque année, 140M d’enfants viennent au monde. Les anomalies congénitales concernent 1 naissance sur 33 dans les pays développés, et dans 50% des cas, elles ne sont pas détectées à l’échographie. De fait, la médecine prénatale est une discipline particulièrement complexe, et les examens sont lourds de responsabilité pour les échographistes. Ils peuvent aussi être source de stress pour les futurs parents.
Riche de plus 5 ans de collaboration entre les experts mondialement reconnus de l’Hôpital Necker et de l’Ecole Polytechnique, Sonio utilise l’intelligence artificielle pour améliorer le dépistage et diagnostic prénatal. Fondée sur des algorithmes brevetés et une base de données experte propriétaire, Sonio veut devenir l’outil de référence pour aider les échographistes à améliorer le dépistage, diminuer les erreurs diagnostiques, et ainsi optimiser le parcours de soin des patients.
Sonio s’est donné pour mission d’améliorer la santé de la femme et de l’enfant en favorisant l’accès et la qualité des soins, par l’innovation technologique, l’expertise médicale et l’intelligence collective.
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
We are looking for a DS/ML Engineer intern to join our Data Science team. Your mission will at the crossing of R&D, ML Engineering and product, supervised by senior ML engineers. You will work on developing of our existing Deep Learning/Computer Vision pipelines using State-of-the-art algorithms.
Your main mission will be to:
• Develop clinical understanding of fetal ultrasound in the anatomical areas you will work on,
• Explore and train different approaches for Detection and Segmentation of anatomical structures and views, and integrate your results in our ML infrastructure (AWS, SageMaker, MLflow),
• Explore the possibility of training Foundation Models for Ultrasound Imaging,
• Run evaluation protocols consistent with the way our models are evaluated during regulatory submissions, and document your experiments so the team can build on them. Publication is possible and encouraged if the results support it.
About the profile
Sonio is a mission-driven company so interest in our mission is critical. Other requirements are:
• Currently in Master 2 / Bac+5 of Engineering School or University, you are majoring in Computer Science or Data Science and are looking for an internship lasting between 5 and 6 months,
• Good knowledge of Machine Learning and Deep Learning algorithms, and the willingness to explore and work on state-of-the-art algorithms,
• Solid Python and PyTorch/HuggingFace, and comfortable with segmentation and detection architectures,
• Strong interest in computer vision and women’s health. A first experience with medical images is a plus,
• You speak English and ideally French.
We move fast and aspire to be transparent over the process - our objective is that the process from the first chat to an offer is no longer than a month. We also aspire to give an answer to every application in a week - if you have not heard from us, please follow up at careers@sonio.ai.
In short
Founding year
2020
Employees
90
Average age
33
Gender
55%
45%