AI Talent Pool

About the role

Doctolib is establishing a dedicated initiative to identify and cultivate a specialized talent pool for upcoming opportunities within our AI and Machine Learning departments. This pool is designed to connect with individuals who share our vision of leveraging advanced technology to simplify daily workflows for healthcare professionals. The primary focus is on developing medical technology that enhances efficiency and expands patient access to high quality care. We are seeking collaborators who are passionate about applying cutting edge methods to solve meaningful problems in the medical sector. This initiative targets individuals who thrive in environments demanding strong analytical rigor and technical depth. Participation in this pool reflects an interest in contributing to impactful, data driven innovation. The selected individuals will play a key role in shaping the future of intelligent systems for healthcare.

Key facts

What you'll do

• Lead the architecture and implementation of large scale projects centered on medical natural language processing, recommendation systems, and clinical automation workflows.
• Drive the application of advanced ML engineering, MLOps, and generative AI methodologies to address complex challenges specific to the healthcare industry.
• Architect and develop sophisticated solutions involving search, ranking, information retrieval, and logical reasoning tailored for medical contexts.
• Conduct research and build prototypes in specialized domains such as knowledge graphs, reinforcement learning, and automatic speech recognition.
• Partner with cross functional teams to translate ambiguous medical problems into well defined technical tasks and deliver robust AI solutions.
• Optimize existing pipelines to improve scalability, reliability, and performance of AI models deployed in production environments.
• Evaluate emerging tools and frameworks, conducting experiments to validate their effectiveness for healthcare specific applications.
• Mentor junior engineers by sharing best practices in prompt engineering, model fine tuning, and production grade AI development.
• Contribute to the definition of technical standards and documentation practices for AI components within the broader product ecosystem.
• Engage with the wider AI community by exploring open source contributions and integrating novel research into practical products.

Requirements

• Hold a Master's degree, PhD, or equivalent in computer science, applied mathematics, data science, or a closely related quantitative field.
• Demonstrate expert level proficiency in Python and substantial experience with deep learning frameworks such as PyTorch, TensorFlow, or Scikit-learn.
• Possess hands on experience working with both open source and closed source large language models, including fine tuning and inference optimization.
• Maintain a highly results oriented mindset, with proven capabilities in analyzing complex problems and designing effective computational solutions.
• Communicate fluently in English, both in written documentation and verbal discussions with international stakeholders.
• Show strict adherence to project timelines and an ability to manage multiple priorities in a fast paced research and development setting.
• Exhibit strong ownership of technical decisions, ensuring alignment between implemented systems and business objectives.
• Display integrity in handling sensitive medical data and a commitment to ethical AI practices.

Nice to have

• Demonstrated background in healthcare applications or experience with medical natural language processing tasks.
• Mastery of Retrieval Augmented Generation techniques, vector search methodologies, and advanced embedding strategies.
• Extensive experience with MLOps and production deployment workflows using containerization tools like Docker, orchestration platforms such as Kubernetes, and experiment tracking systems like MLflow.
• A record of publishing research in leading AI conferences or notable journals, or substantial contributions to recognized open source projects.

Practical notes

Doctolib is an equal opportunity employer and welcomes applicants regardless of gender, religion, age, sexual orientation, ethnicity, disability, or origin. If you have a disability and require adjustments during the interview process, please inform us. Data submitted during application is processed in accordance with our privacy policy; inquiries regarding data rights can be directed to hr.dataprivacy@doctolib.com.