Depuis octobre 2013, FeetMe développe des dispositifs médicaux connectés pour améliorer la mobilité. Avec le vieillissement de la population et le développement des maladies chroniques, la perte de mobilité est un enjeu de santé publique majeur.
Leur ambition ? Devenir le premier partenaire mondial dans la détection précoce des troubles de la marche et de l’équilibre et l’amélioration de leur prise en charge.
Comment ? En développant des semelles avec des capteurs de pression et de mouvement et un logiciel embarqué qui analyse la marche et récolte des données en vie réelle.
FeetMe is looking for a Machine Learning and Signal Processing Engineer to join our team to participate in the development of new functionalities of our products as well as new technologies and new products.
Our connected smart insoles contain pressure and motion sensors, and your main mission will be to extract from these signals additional information and results, which then will become a part of the product features. The example of such features can be gait parameters, biofeedback rehabilitation exercises or user’s activities recognition. These developments will require the use of both machine learning and classical signal processing tools and will typically imply time series analysis. Calculation power based on the algorithm complexity will also be considered (CPU, RAM, and real time computing) and algorithm optimisations might be necessary sometimes. For a successful carrying out of the mission close interaction with the developers as well as the data scientists will be essential. Last, but not least, the position will demand thorough validation and documentation process both of the code and of the algorithm performance.