Senior Staff Machine Learning Engineer - Clinical - AI Teams (x/f/m)

We are looking for a Senior Staff Machine Learning Engineer to join the Clinical team in the AI and Machine Learning Department. You'll lead the technical direction of AI systems that enhance clinical decision-making and patient care. You'll tackle the hardest problems in healthcare AI, from building voice-powered consultation assistants to establishing LLM evaluation frameworks that ensure clinical safety and efficacy. This role combines deep R&D with strategic technical leadership, shaping how Doctolib deploys AI in regulated healthcare environments.

Your responsibilities include but are not limited to:

Technical Strategy & Architecture

• Own the long-term technical roadmap for clinical ML systems, from model architecture selection to production deployment patterns
• Drive strategic build vs. buy decisions, balancing custom development with foundation model APIs
• Define standards for safe rollout in healthcare contexts: shadow testing, staged deployment, and human-in-the-loop workflows

End-to-End ML Delivery

• Lead design and implementation of LLM-powered clinical agents (consultation summarization, clinical coding, evidence-grounded recommendations)
• Establish rigorous evaluation frameworks using real-world clinical datasets, ensuring outputs meet clinical accuracy and safety standards
• Build production infrastructure: model and prompt versioning, guardrails, uncertainty quantification, cost optimization, and observability
• Define a bold strategy for online and offline performance objectives to reach new levels of healthcare professionals satisfaction

Leadership & Impact

• Mentor Staff or Senior ML Engineers and Applied Scientists, elevating technical standards across the organization
• Lead cross-functional initiatives spanning Product, Medical Affairs, Legal, and Compliance teams
• Translate clinical needs into research questions and production systems that measurably improve patient outcomes
• Partner with our medical, legal, and compliance teams to meet EU regulatory expectations (e.g., GDPR, MDR, upcoming EU AI Act) and market standards.