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

Your Impact

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

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

Senior MLOps Engineer - Data Ingestion

Your Impact

What you'll build

Senior MLOps Engineer - Data Ingestion

Your Impact

What you'll build

Life at Doctolib Tech

What you'll bring

What we offer

Our interview process

Job details

We welcome everyone

Your data privacy

Doctolib

Doctolib

Benefits

Doctolib