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

📋 Job Overview

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.

🏢 About Doctolib

Doctolib is a leading healthcare technology company that provides online appointment scheduling and telemedicine services. We are committed to improving access to healthcare for everyone through innovative technology solutions.

🎯 The Role

Your responsibilities include but are not limited to:

✅ Key Responsibilities

• 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
• 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

📌 Required Qualifications

• 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

⭐ Desirable Experience

• 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

🎁 Benefits

• Free comprehensive health insurance (basic package) for you and your children
• 25 days of paid vacation per year, plus up to 14 days of RTT
• Free mental health and coaching services through our partner Moka.care
• Work from abroad for up to 10 days per year thanks to our flexibility days policy
• Lunch vouchers (Swile card) worth €8.50 per working day, with €4.50 covered by Doctolib
• A subsidy from the work council to refund part of the membership to a sport club or a creative class
• 50% reimbursement of your public transport subscription
• ParentCare Program: Enjoy full salary coverage (100%) during your first month of birth leave, and 75% during the second, covered by Doctolib
• Enrollment in Doctolib's long-term employee value sharing plan called DoctoGrowth
• For caregivers and workers with disabilities, a package including an adaptation of the remote policy, extra days off for medical reasons, and psychological support
• Relocation support in case of international mobility
• Access to the best AI tools for coding, development and dedicated training

🛂 Visa & Eligibility

Doctolib is committed to equal opportunity and welcomes applications from all qualified candidates regardless of nationality, work authorization status, or background. We will consider sponsorship for eligible candidates.