Senior MLOps Engineer

About

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.

Responsibilities

• 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

Requirements

• At least 7 + years as an MLOps Engineer or ML Platform Engineer with proven production model lifecycle management experience
• Expert‑level experience with ML orchestration tools (MLflow, Braintrust, or similar) for batch processing and inference pipelines
• Strong Site Reliability Engineering (SRE) foundation with focus on operations excellence, reliability, and observability
• Expertise in Python for automation and ML pipeline scripting
• Strong proficiency with infrastructure‑as‑code tools such as Terraform and container orchestration (Kubernetes)
• Experience with model evaluation frameworks and golden dataset management
• Solid understanding of cloud infrastructure (preferably GCP, AWS, or Azure)
• Excellent problem‑solving skills with focus on identifying and resolving infrastructure bottlenecks
• Fluency in English

Nice to Have

• Production LLM or custom model deployment experience
• Knowledge of data security and privacy frameworks (GDPR, data anonymization, pseudonymization)
• Experience building and monitoring security services and threat detection systems
• Strong communication and mentoring skills to drive knowledge transfer across teams

Benefits

• Free comprehensive health insurance for you and your children
• 25 days of paid vacation per year, plus up to 14 days of RTT
• Free mental health and coaching services through our partner Moka.care
• Work from abroad for up to 10 days per year thanks to our flexibility days policy
• Lunch vouchers (Swile card) worth €8.50 per working day, with €4.50 covered by Doctolib
• A subsidy from the work council to refund part of the membership to a sport club or a creative class
• 50 % reimbursement of your public transport subscription
• Parent Care Program: receive one additional month of leave on top of the legal parental leave
• Package for caregivers and workers with disabilities, including adaptation of the remote policy, extra days off for medical reasons, and psychological support
• Relocation support in case of international mobility
• Access to the best AI tools for coding, development and dedicated training

Interview Process

• Recruiter Interview
• Technical Case Study Interview
• System Design Interview
• Behavioral Interview
• At least one reference check

Job Details

• Permanent position (CDI)
• Tech stack: Python
• Full‑time
• Nantes & Paris (Hybrid Policy: 2 days remote per week)
• Start date: as soon as possible