Staff ML Engineer, Retrieval - Medical Knowledge Platform

EngineersOfAI; France; Sur place; EUR 90 000 - 140 000; Plein temps

Avantages offerts par ce poste

Health insurance

Vacation days

RTT days

Résumé du poste

Doctolib is seeking a Staff Machine Learning Engineer - Retrieval to join our AI team and advance the Medical Knowledge Platform. You will ground clinical AI decisions in validated HAS guidelines and peer-reviewed studies, building robust retrieval systems that scale to massive medical knowledge.

You’ll contribute to clinical safety and reliability across Europe. You’ll design and maintain indexing pipelines, work on vector embeddings and re-ranking, and own end-to-end retrieval performance from

Qualifications

• Proven production experience building and scaling search and retrieval systems.
• Deep dual expertise in offline indexing and online retrieval across pipelines.
• Hands-on with Elasticsearch, Solr, Vertex AI, vector search and embeddings.
• Experience designing custom re-rankers and indexing pipelines.
• Senior or Staff level with autonomy and technical depth.

Responsabilités

• Build and own Doctolib’s Medical Knowledge Platform grounding AI decisions in medical sources.
• Design and maintain indexing pipelines and retrieval systems across the full stack.
• Operate at scale: handle 100M+ documents, 50+ req/s, sub-300ms latency.
• Develop deep RAG systems and robust retrieval evaluation frameworks.
• Work across vector embeddings, vector search, re-ranking, and query rewriting.

Connaissances

Search & retrieval systems

Senior/Staff level

Distributed systems

Outils

Elasticsearch

Solr

Vertex AI

vector search

embeddings

re-ranking

query processing

Rails

TypeScript

Java

Python

Kotlin

Swift

React Native

Description du poste

Doctolib is seeking a Staff Machine Learning Engineer - Retrieval to join our AI team and advance the Medical Knowledge Platform. You will ground clinical AI decisions in validated HAS guidelines and peer-reviewed studies, building robust retrieval systems that scale to massive medical knowledge.

You’ll contribute to clinical safety and reliability across Europe. You’ll design and maintain indexing pipelines, work on vector embeddings and re-ranking, and own end-to-end retrieval performance from