Senior MLOps Engineer - Data Ingestion - Paris

Responsibilities

• 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
• 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 .

Requirements

• 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
• You have a strong Site Reliability Engineering (SRE) foundation with focus on operations excellence, reliability, and observability
• You have expertise in Python for automation and ML pipeline scripting
• You have strong proficiency with infrastructure-as-code tools such as Terraform and container orchestration (Kubernetes)
• You have experience with model evaluation frameworks and golden dataset management
• You have a solid understanding of cloud infrastructure (preferably GCP, AWS, or Azure)
• You have excellent problem-solving skills with focus on identifying and resolving infrastructure bottlenecks
• You are fluent in English
• It would be fantastic if you:
• Have production LLM or custom model deployment experience
• Have knowledge of data security and privacy frameworks (GDPR, data anonymization, pseudonymization)
• Have experience building and monitoring security services and threat detection systems
• Have strong communication and mentoring skills to drive knowledge transfer across teams

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