Senior ML Engineer: Scalable AI for Patient Care

Doctolib

Paris

Hybride

EUR 70 000 - 90 000

Plein temps

14 jours+
Générateur de candidature

Une candidature sur mesure pour ce poste — un CV et une lettre de motivation personnalisés qui correspondent à l’offre.

Passez les filtres ATS

Avantages offerts par ce poste

Free comprehensive health insurance
25 days paid vacation plus RTT
Free mental health and coaching services
Lunch vouchers worth €8.50
50% reimbursement of public transport
Access to the best AI tools

Résumé du poste

Doctolib is hiring a Senior Machine Learning Engineer to join their Patient Solutions team. You will lead the development of AI and ML systems to enhance healthcare access, working on intelligent solutions and large-scale retrieval systems.

This position requires 7+ years of experience in ML and AI, with a focus on production-scale models and modern retrieval methods. The role offers a hybrid work setup, emphasizing both innovation and measurable impacts on patient care.

Qualifications

  • Experience taking models from prototype to production at scale.
  • Strong track record in modern retrieval stacks and hybrid search.
  • Proficient in fine-tuning ML models and developing AI systems.

Responsabilités

  • Design and implement ML and AI solutions aligned with patient product goals.
  • Build and maintain large-scale retrieval pipelines.
  • Deploy solutions to production in collaboration with the ML platform team.

Connaissances

Machine Learning
Deep Learning
AI Engineering
Information Retrieval
English Fluency

Formation

7+ years in Machine Learning or AI Engineering

Outils

Python
TypeScript
Java
Kotlin
Swift
React Native

Description du poste

Doctolib is hiring a Senior Machine Learning Engineer to join their Patient Solutions team. You will lead the development of AI and ML systems to enhance healthcare access, working on intelligent solutions and large-scale retrieval systems.

This position requires 7+ years of experience in ML and AI, with a focus on production-scale models and modern retrieval methods. The role offers a hybrid work setup, emphasizing both innovation and measurable impacts on patient care.

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