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

About this role

What you’ll do 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.