Senior Machine Learning Engineer - Applied AI & LLMs (x/f/m)

EngineersOfAI; Paris; Sur place; EUR 60 000 - 90 000; Plein temps

Résumé du poste

EngineersOfAI is seeking a Senior Machine Learning Engineer to enhance how individuals access quality care through AI. You will join the ML Engineering team in Patient Solutions, focusing on developing intelligent patient-facing solutions. Your role involves designing ML systems to create impactful health management tools.

Key responsibilities include implementing solutions, maintaining retrieval pipelines, and deploying AI systems in collaboration with the ML platform team. Your work will significantly contribute to improving the efficiency and quality of patient care across Europe.

Qualifications

• Expertise in designing and implementing ML and AI systems.
• Experience with large-scale retrieval pipelines and hybrid search.
• Proficient in developing and evaluating LLM and VLM models.

Responsabilités

• Design and implement ML solutions aligned with product goals.
• Build and maintain retrieval pipelines and AI systems.
• Deploy solutions to production with reliability and performance.

Connaissances

Machine Learning

AI Solutions Implementation

Vector Databases

Prompt Engineering

Controlled Experiments

Outils

W&B

MLFlow

Braintrust

Description du poste

Your Impact

We are looking for a Senior Machine Learning Engineer to join the ML Engineering team in Patient Solutions.

Your mission will be to improve how people access quality care and manage their health over time by building and leading AI and ML systems that create real, measurable impact. You will work in a feature team developing intelligent patient-facing solutions, from smart practitioner discovery to long-term care management, playing a key technical role in shaping how we scale our AI capabilities 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:

• 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, Mixture-of-Experts (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

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 y