AI Research Scientist

Join Sprinter, a leading AI healthcare company, as an AI Research Scientist. In this role, you will develop and own a research agenda aligned with the company's strategy, focusing on advancing the methodological frontier of AI in healthcare. You will work on novel architectures, training techniques, validation studies, and methods that will ultimately graduate into production systems. The ideal candidate will have a strong technical background, experience in healthcare validation standards, and a passion for making a meaningful impact in the field.

• Développer et posséder un agenda de recherche aligné sur la stratégie de l'entreprise, en identifiant les problèmes ouverts et en concevant des expériences.
• Produire des publications, des brevets, des études de validation par les pairs et d'autres artefacts de preuve, et traduire la recherche prometteuse en méthodes et outils.
• Collaborer avec des partenaires cliniques sur des études de validation, y compris le travail pouvant impliquer un examen IRB, la gouvernance des données, la validation externe.
• This role is ideal for someone who has demonstrated strong research taste, deep technical foundations, and the ability to turn open-ended problems into rigorous scientific contributions
• The ideal candidate is deeply technical, scientifically rigorous, and excited to collaborate closely with clinicians, product leaders, and applied AI teams
• Understanding of healthcare validation standards, including the importance of external validation, prospective evaluation, data governance, and real-world deployment constraints
• Strong engineering ability, including the ability to run your own experiments at scale
• Comfort working in open-ended, ambiguous environments where the right research direction may need to be shaped from first principles
• Demonstrated ability to produce novel research, including identifying open problems, designing rigorous experiments, and writing work to a peer-review standard
• Deep ML foundations and genuine depth in at least one relevant area, such as LLMs, agents, uncertainty, causality, multimodal learning, clinical AI, or related fields
• Interest in clinical collaboration and applied healthcare impact
• Strong research taste and the ability to distinguish incremental work from meaningful methodological contribution
• First-author publications at top technical venues such as NeurIPS, ICML, ICLR, ACL, or related conferences
• Publications in leading clinical AI or healthcare venues such as Nature Medicine, NEJM AI, npj Digital Medicine, CHIL, MLHC, or similar
• Experience in academia, industry research labs, or research-heavy teams at AI-native healthcare companies
• Experience collaborating with clinicians, clinical researchers, or healthcare operators
• Dual literacy across machine learning and clinical collaboration
• Familiarity with IRB processes, clinical data governance, or healthcare model validation