Staff ML Engineer for Medical Knowledge Retrieval

Doctolib; Levallois-Perret; Hybride; EUR 120 000 - 180 000; Plein temps

Avantages offerts par ce poste

Health insurance

Vacation 25 days

Remote work 2 days/wk

Relocation support

Lunch vouchers

Résumé du poste

Doctolib is seeking a Staff Machine Learning Engineer - Retrieval to build and scale the Medical Knowledge Platform, grounding clinical AI decisions in HAS guidelines and medical studies. You will own the retrieval stack in a cross-functional team across Europe, shaping the future of healthcare AI.

You will work with vector embeddings, indexing pipelines, re-ranking, and deep RAG systems to deliver fast, reliable clinical search experiences for health professionals and patients.

Qualifications

• Proven production experience building and scaling search and retrieval systems in high-traffic environments.
• Full ownership of offline indexing and online retrieval pipelines.
• Hands-on with the retrieval tech stack: Elasticsearch, Solr, vector search and embeddings.
• Experience at a Senior or Staff level with autonomy and depth.

Responsabilités

• Own and scale Doctolib’s Medical Knowledge Platform, grounding AI decisions in medical sources and studies.
• Design and maintain indexing pipelines and end-to-end retrieval stacks.
• Achieve sub-300ms latency with systems handling 100M+ documents and 50+ req/s.
• Build and optimize re-rankers and query processing, plus evaluation frameworks.
• Develop deep Retrieval/ RAG systems, including vector embeddings and query rewriting.

Connaissances

Search & retrieval systems

Production-grade systems

Senior/Staff level

Distributed computing

Outils

Elasticsearch

Solr

Vertex AI

Vector search

Embeddings

Description du poste

Doctolib is seeking a Staff Machine Learning Engineer - Retrieval to build and scale the Medical Knowledge Platform, grounding clinical AI decisions in HAS guidelines and medical studies. You will own the retrieval stack in a cross-functional team across Europe, shaping the future of healthcare AI.

You will work with vector embeddings, indexing pipelines, re-ranking, and deep RAG systems to deliver fast, reliable clinical search experiences for health professionals and patients.