Senior MLOps Engineer - Data Ingestion - Paris

Free resume; Paris; Hybride; EUR 90 000 - 130 000; Plein temps

Avantages offerts par ce poste

Health insurance for you and family

Paid vacation + RTT

Mental health support

Work from abroad up to 10 days/year

Lunch vouchers (Swile)

Résumé du poste

Doctolib seeks a Senior MLOps Engineer to join the Panda Team in the Data & AI Platform group. You will design end-to-end ML pipelines, implement data anonymization within ingestion, and ensure secure data exports and monitoring across millions of users.

The role combines production ML, data security, and infra automation in a hybrid Paris/Nantes setup. You will mentor teammates, work with Python, Kubernetes, and Terraform, and advance our cloud-native data infrastructure while upholding

Qualifications

• At least 7+ years as an MLOps Engineer or ML Platform Engineer with production lifecycle experience.
• Expert-level experience with ML orchestration tools (MLflow, Braintrust, or similar).
• Strong Site Reliability Engineering (SRE) foundation focused on reliability, observability.
• Expert in Python for automation and ML pipeline scripting.
• Proficiency with infrastructure-as-code tools such as Terraform and container orchestration (Kubernetes).
• Experience with cloud infrastructure (GCP, AWS, or Azure).
• Fluent in English.

Responsabilités

• Design and implement end-to-end ML model pipelines in production (LLM and custom models).
• Own data pseudo-anonymization architecture within ingestion services, converting Tier 0 to Tier 1.
• Build and maintain secure data export services with ML-based threat detection.
• Manage golden datasets and model evaluation frameworks for anonymization quality.
• Build and maintain data pipelines to extract, transform, and load data from multiple sources.
• Implement automation/orchestration tools to streamline provisioning (MLflow/Braintrust or similar).
• Monitor data and ML platforms for performance, reliability, and security; troubleshoot issues.
• Mentor team members on MLOps practices.

Connaissances

MLOps

Python

Kubernetes

Terraform

SRE

MLflow

Data anonymization

Cloud

Mentoring

Outils

MLflow

Braintrust

Kubernetes

Terraform

Description du poste

# Senior MLOps Engineer - Data Ingestion - ParisDoctolib· Paris, France· Posted 4/7/2026 On-site (Paris)contractLang: enApply on Company SiteTailor My Resume for this RoleDirect company application on jobs.ashbyhq.com. Zero third-party aggregator forms.## Job Description## **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* 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 EnglishIt 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## **What we offer*** 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* For caregivers and workers with disabilities, a package including an 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## **Our interview process*** Recruiter Interview* Technical Case Study Interview* System Design Interview* Behavioral Interview* At least one reference checkWe want your experience to be clear, respectful, and transparent. Learn more about our hiring process on our candidate experience page.## **Job details*** Permanent position (CDI)* Tech stack: Python* Full-time* Nantes & Paris (Hybrid Policy: 2 days remote / week)* Start date: as soon as possible