At Lifen, we believe that medical data has the power to revolutionize the healthcare system, but only if it is accessible. More accessible data leads to reduced administrative burdens, improved care coordination, and faster scientific discoveries.Since 2015, our mission has been to unlock this potential. Our AI-driven solutions enable healthcare professionals to effortlessly share medical information and empower researchers to accelerate clinical discoveries, impacting millions of patients in France every day. As we prepare to expand across Europe, our success hinges on two key factors: our teams and our mission.Today, over 150 individuals work both onsite and remotely to unleash the potential of health data. We have connected 800 hospitals and 150,000 healthcare professionals, and we are just getting started. We seek individuals who embrace complexity, are eager to tackle challenging problems, and are ready to build the future of healthcare collaboration.Our AI TeamThe AI team at Lifen delivers over one million real-time predictions daily, powering our flagship product, Lifen Document, which transforms the exchange of medical reports among practitioners in France.With six years of experience in handling medical data, our team consisting of 5 ML Engineers and 1 Engineering Manager excels at building robust and secure models that drastically streamline healthcare professionals' administrative tasks.From layout extraction to pseudonymization, fine-tuning LLM for medical data extraction, and applying NLP algorithms to structure documents, we encompass the entire intelligent data processing chain in healthcare. What You'll Do with UsAt Lifen, Machine Learning addresses concrete challenges in processing medical documents, utilizing exploratory approaches in NLP and computer vision. During this internship, you will work on innovative topics at the intersection of research and industrial application. On a daily basis, you will:• Conduct experiments on NLP and vision challenges, exploring new approaches (calibration, confidence and context attribution in LLMs, reinforcement learning, multimodal models...).• Carry out thorough scientific monitoring and implement methods from recent publications, adapting them to our specific use cases in the medical field.• Rigorously evaluate the performance of your models...
Dec 1, 2025