Senior MLOps Engineer - Data Ingestion - Paris

Your Impact

We are looking for a Senior MLOps Engineer to join the Panda Team (Data & ML Operations) in Data & AI Platform team .

Your mission will be to build and maintain secure ML pipelines in production, transforming how we handle healthcare data at scale. You will work in a feature team developing critical data infrastructure that enables data-driven decision-making while protecting patient privacy across millions of users.

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 build

Your responsibilities include but are not limited to:

Design and implement end-to-end ML model pipelines in production (LLM and custom models) with robust deployment, evaluation, and monitoring frameworks

Own data pseudo-anonymization architecture within ingestion services, converting Tier 0 (personal identifiers) to Tier 1 (anonymized data) while ensuring data quality and model performance

Build and maintain secure data export services with ML-based threat detection to prevent attack vectors (SQL injection, etc.) using adaptive models rather than manual rules

Manage golden datasets and implement production model evaluation frameworks to ensure anonymization quality and system reliability

Build and maintain data pipelines that efficiently extract, transform, and load data from various sources, handling multiple data formats (text, images, audio, video)

Implement automation and orchestration tools using ML orchestration platforms (MLflow, Braintrust, or similar) to streamline infrastructure provisioning and reduce manual effort

Monitor data and ML platforms for performance, reliability, and security; identify and troubleshoot issues proactively

Mentor team members on MLOps expertise and best practices to reduce knowledge silos and build organizational capability

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 .

What you'll bring

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 at least 7+ years as an MLOps Engineer or ML Platform Engineer with proven production model lifecycle management experience

You have expert-level experience with ML orchestration tools (MLflow, Braintrust, or similar) for batch processing and inference pipelines