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# [Data - FR] Senior Machine Learning Engineer - Orchestration

- **Company:** DOCTOLIB SAS
- **Location:** Paris, France
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** Java (Programming Language), Artificial Intelligence, Computer Vision, Distributed Systems, Mobile Application Software, Python (Programming Language), Machine Learning, TypeScript, Large Language Models, Multi-Agent Systems, Swift (Programming Language), Kotlin, Information Technology, React Native, GPT
- **Published:** July 5, 2026
- **Apply:** https://fr.indeed.com/viewjob?jk=ca739c982047047d

## About the Role

* MSc or PhD in Computer Science, Machine Learning, Data Science, or related field
 * 7+ years of hands-on experience working with large language models (e.g., GPT, Claude, Llama, or BERT-like architectures)
 * Proven experience in evaluating agentic or reasoning systems (e.g., autonomous agents, tool-using LLMs, dialogue systems, or task-oriented assistants)
 * Strong track record in experiment design, metric definition, and evaluation automation
 * Ability to bridge research and production, influencing modeling and product decisions
 * Excellent communication skills and a collaborative mindset

Now it would be fantastic if:

 * You have experience in the clinical or medical domain and sensitivity to ethical or regulatory challenges in healthcare AI

## Description

As a Senior/Staff Machine Learning Engineer, you'll play a key role in designing, implementing, and scaling the evaluation framework that ensures our AI Health Companion behaves safely, reliably, and helpfully for millions of patients and practitioners.

You'll join a cross-functional team of Machine Learning Engineers, Product Engineers, and Medical Experts to build robust evaluation pipelines for agentic AI systems - models capable of reasoning, planning, and interacting with complex healthcare data.

Your responsibilities include, but are not limited to:

 * Define and own the evaluation strategy for our AI agentic system - metrics, protocols, datasets, and tooling
 * Implement and maintain automated evaluation pipelines to monitor model quality, safety, and alignment across iterations
 * Run systematic experiments to assess reasoning, factuality, robustness, and user experience
 * Collaborate closely with model developers and research scientists to provide insights and drive iterative improvement
 * Contribute to research and internal knowledge sharing on LLM evaluation methodologies and best practices

About our tech environment

 * Our solutions are built on a single fully cloud-native platform that supports web and mobile app interfaces, multiple languages, and is adapted to the country and healthcare specialty requirements. To address these challenges, we are modularizing our platform run in a distributed architecture through reusable components
 * 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!


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