Senior Staff Machine Learning Engineer - Clinical - AI Teams (x/f/m)
DoctolibParis, Paris, FrancePosted 30 March 2026
Job Description
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 RD 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.
Who you are
Before you read on, if you don't have the exact profile described below, but you feel this job description matches your skill set, we still encourage you to apply.
You have 10+ years in ML/AI with 3+ years at Staff+ or Principal level leading complex, multi-team technical initiatives
You have a PhD in Computer Science, AI, Statistics, or related field (or equivalent research experience)
You have deep expertise in at least two of: clinical NLP, LLM fine-tuning and evaluation, automatic speech recognition, RAG systems, or reinforcement learning
You are expert in Python, PyTorch/Transformers for training, vLLM/similar for inference with a track record deploying ML systems in production (AWS/GCP)
You have exceptional communication skills and are able to align diverse stakeholders and explain complex technical decisions
Now it would be fantastic if you have:
Publications in top-tier ML/AI conferences (NeurIPS, ICLR, ACL) or medical informatics venues
Experience with EU healthcare regulations (GDPR, MDR, AI Act)
Prior work with clinical data or healthcare applications
What we offer
Free comprehensive health insurance for you and your children
Parent Care Program: receive one additional month of leave on top of the legal parental leave
Free mental health and coaching services through our partner Moka.care
For caregivers and workers with disabilities, a package including an adaptation of the remote policy, extra days off for medical reasons, and psychological support
Work from abroad for up to 10 days per year thanks to our flexibility days policy
Work Council subsidy to refund part of sport club membership or creative class
Up to 14 days of RTT
A subsidy from the work council to refund part of the membership to a sport club or a creative class
Lunch voucher with Swile card
The interview process
HR Screen
Hiring Manager Interview
Behavioral Inte ... (truncated, view full listing at source)
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