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

Responsibilities

• We are looking for a Senior Machine Learning Engineer to join the ML Engineering team in Patient Solutions .
• Working in the tech team at Doctolib means building innovative products and features to improve the daily lives of care teams and patients.
• 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

Requirements

• 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 you to apply.
• You'll be a great fit if you:
• You have 7+ years of experience in Machine Learning, Deep Learning, or AI Engineering, with a strong track record of taking models from prototype to production at scale
• You have strong experience in Information Retrieval and modern retrieval stacks: hybrid search (sparse + dense), large-scale embeddings and vector databases, multi-stage retrieval and re-ranking pipelines, RAG architectures, and tool/MCP-based integrations
• You are proficient in LLM and VLM application development: fine-tuning, MoE architectures (via LiteLLM or Model Garden), knowledge distillation, prompt engineering, and systematic benchmarking of LLM/VLM systems
• You have hands-on experience building and orchestrating agentic AI systems (e.g., using ADK)
• You demonstrate strong scientific rigor: designing metrics aligned with product goals, running controlled experiments, and communicating results clearly to both product and engineering stakeholders
• You have experience operating large-scale applications in production (monitoring, reliability, performance, observability), bring strong analytical skills, and approach your work with a user-first mindset. You are fluent in English
• It would be fantastic if you:
• Have experience in B2C marketplace environments
• Have experience in other ML methodologies: pattern mining, recommendation systems, experimentation, or causal inference
• Life at Doctolib Tech
• Our solutions are built on a single fully cloud-native platform that supports web and mobile app interfaces, multiple languages, and is adapted to country and healthcare specialty requirements.
• Our stack is composed of Rails, TypeScript, Java, Python, Kotlin, Swift, and React Native.
• We leverage AI ethically across our products to empower patients and health professionals. Discover our AI vision here .
• Want to learn more about our tech culture and environment? Visit the Doctolib Tech site .

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