Senior MLOps Engineer – Data Ingestion – Paris

Sourced from careers.doctolib.com

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