Senior ML Engineer: Applied AI & LLMs for Patient Care

Doctolib; Levallois-Perret; Hybrid; EUR 110,000 - 170,000; Full time

Benefits offered by this job

Free comprehensive health insurance (±

25 days paid vacation per year

Lunch vouchers (Swile)

Relocation support for international移

DoctoGrowth equity program

Public transport subsidy

Mental health and coaching services

Flexible days to work abroad

Payment of RTT days

Caregiver accommodations and support

Job summary

Doctolib is seeking a Senior Machine Learning Engineer to join the ML Engineering team within Patient Solutions in Levallois-Perret. You will lead and build AI-driven patient-facing solutions, shaping how care is accessed and managed across Europe.

The role emphasizes scalable ML systems, retrieval stacks, LLM/VLM work, and production-grade reliability. Hybrid work is offered, with a strong focus on measurable impact and collaboration with the Doctolib Tech organization.

Qualifications

• 7+ years of experience in Machine Learning, Deep Learning, or AI Engineering and a proven track record of moving models from prototype to production at scale.
• Strong experience in Information Retrieval and modern retrieval stacks: hybrid search, embeddings, vector databases, multi-stage retrieval and re-ranking pipelines, RAG architectures, and tool/MCP-based integrations.
• Proficiency in LLM and VLM application development: fine-tuning, MoE architectures, knowledge distillation, prompt engineering, and benchmarking of LLM/VLM systems.
• Hands-on experience building and orchestrating agentic AI systems (e.g., using ADK).
• Strong scientific rigor: designing metrics aligned with product goals, running controlled experiments, and communicating results to product/engineering stakeholders.
• Fluency in English; experience operating large-scale production applications with monitoring, reliability, and observability.

Responsibilities

• Design and implement ML and AI solutions aligned with patient product goals, covering search, retrieval, and personalized care pathways.
• Build and maintain large-scale retrieval pipelines, including hybrid search, embedding systems, vector databases, and multi-stage re-ranking architectures.
• Develop, fine-tune, and evaluate LLM and VLM models using techniques such as knowledge distillation, MoE architectures, and prompt engineering.
• Build and orchestrate agentic AI systems, integrating external data and capabilities through tools and MCP-based integrations.
• Define metrics aligned with product goals, run controlled end-to-end experiments using W&B, MLFlow, or Braintrust, and communicate findings to guide product and technical decisions.
• Deploy solutions to production in collaboration with our ML platform team, ensuring reliability, observability, and performance at scale, and act as a technical reference to elevate the team's standards and practices.

Skills

Machine Learning

Deep Learning

Information Retrieval

LLM/VLM development

Agentic AI systems

Production reliability

Tools

W&B

MLFlow

Braintrust

Job description

Doctolib is seeking a Senior Machine Learning Engineer to join the ML Engineering team within Patient Solutions in Levallois-Perret. You will lead and build AI-driven patient-facing solutions, shaping how care is accessed and managed across Europe.

The role emphasizes scalable ML systems, retrieval stacks, LLM/VLM work, and production-grade reliability. Hybrid work is offered, with a strong focus on measurable impact and collaboration with the Doctolib Tech organization.