Staff Machine Learning Engineer - Retrieval

Your mission will be to ground clinical AI decisions in validated, trusted medical sources from HAS guidelines and learned society recommendations to peer-reviewed clinical studies. You will work in a feature team developing Doctolib’s Medical Knowledge Platform , contributing directly to the reliability and safety of AI-powered healthcare experiences used by hundreds of thousands of health professionals and millions of patients across Europe.

Working in the tech team at Doctolib means building innovative products and features to improve the daily lives of care teams and patients., * Build and own Doctolib’s Medical Knowledge Platform, designing the systems that ground clinical AI decisions in validated medical sources (HAS guidelines, learned society recommendations, clinical studies)

• Design and maintain both indexing pipelines and retrieval systems, ensuring end-to-end ownership across the full retrieval stack
• Operate at scale: architect and optimize systems handling 100M+ documents, 50+ req/s, and sub-300ms latency requirements
• Build custom re-rankers, optimize query processing pipelines, and design robust retrieval evaluation frameworks
• Engineer deep RAG systems from the ground up - going well beyond off-the-shelf components to tackle real medical knowledge complexity
• Work across the full retrieval stack: vector embeddings, vector search, re-ranking, query expansion and rewriting, * Our solutions are built on a single fully cloud-native platform that supports web and mobile app interfaces, multiple languages, and is adapted to country and healthcare specialty requirements.
• Our stack is composed of Rails, TypeScript, Java, Python, Kotlin, Swift, and React Native.
• We leverage AI ethically across our products to empower patients and health professionals. Discover our AI vision here .

• Have proven production experience building and scaling search & retrieval systems in a real-world, high-traffic environment
• Bring deep dual expertise in both offline indexing and online retrieval; you own the full pipeline, not just one side of it.
• Are genuinely hands-on with the retrieval tech stack: Elasticsearch, Solr, Vertex AI, vector search, embeddings, re-ranking and query processing.
• Have gone beyond commodity RAG; you’ve built custom re-rankers, optimized indexing pipelines, or engineered query processing solutions that required real technical depth.
• Have operated at Senior or Staff level, with the autonomy and technical depth that comes with it.

It would be fantastic if you:

• Have experience working with medical knowledge sources, clinical databases, or healthcare information systems
• Have contributed to evaluation frameworks and benchmarks for retrieval quality or AI outputs in regulated or high-stakes environments
• Have worked in a multi-lingual retrieval context or with domain-specific ontologies

• 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

Our interview process

• Recruiter Screen (45’)
• Live Coding Interview (75’)
• System Design Interview (75’)
• Behavioural Interview (75’)
• Reference Check & Offer

We want your experience to be clear, respectful, and transparent. Learn more about our hiring process on our candidate experience page .