Staff Machine Learning Engineer - Retrieval (x/f/m)

Set a new pulse for healthcare!

We are looking for a Staff Machine Learning Engineer - Retrieval to join our AI team working on Clinical decision support and Medical Knowledge.

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.

What you'll do

Your responsibilities include but are not limited to

• 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

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'll be a great fit if you

• 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