Senior Machine Learning Engineer

At Doctolib, we're on a mission to transform how healthcare is delivered by harnessing the power of AI. 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

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!

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

Free mental health and coaching services through our partner Moka.care For caregivers and workers with disabilities, a package including an adaptation of the remote policy, extra days off for medical reasons, and psychological support Work from EU countries and the UK for up to 10 days per year, thanks to our flexibility days policy Work Council subsidy to refund part of sport club membership or creative class Up to 14 days of RTT Lunch voucher with Swile card

The interview process

Recruiter interview Technical Deep Dive Data System Design Behavioral Interview At least one reference check