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Design and implement secure end-to-end ML pipelines for LLMs and custom models, focusing on data ingestion and pseudo-anonymization. Build and maintain secure data export services with ML-based threat detection and manage production model evaluation frameworks.
Requires 7+ years of experience as an MLOps or ML Platform Engineer with expertise in Python, Terraform, Kubernetes, and ML orchestration tools. A strong SRE foundation and experience with cloud infrastructure (GCP, AWS, or Azure) are essential.
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.
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
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.
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
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
Recruiter Interview
Technical Case Study Interview
System Design Interview
Behavioral Interview
At least one reference check
We want your experience to be clear, respectful, and transparent. Learn more about our hiring process on our candidate experience page.
Permanent position (CDI)
Tech stack: Python
Full-time
Nantes & Paris (Hybrid Policy: 2 days remote / week)
Start date: as soon as possible
At Doctolib, we are committed to improving access to healthcare for everyone. This translates into our recruitment process. We evaluate candidates based solely on qualifications and motivation, without any form of discrimination.
The more diverse ideas are heard, the more our product will truly improve healthcare for all. You are welcome to apply to Doctolib, regardless of your gender, religion, age, sexual orientation, ethnicity, or disability.
To ensure equal opportunities, we invite you to exclude personal information (e.g., pictures, age) from your applications. If you require any accommodation, please let us know for support during the hiring process.
Join us in building the healthcare we all dream of!
All information provided is processed by Doctolib for application management. For data processing details, click here: France. Please contact hr.dataprivacy(at)doctolib.com for inquiries or to exercise your rights.
We’re a B Corp company committed to build together the healthcare we all dream of. More than 2,900 Doctolibers in France, Germany, Italy, and the Netherlands are helping to improve the daily lives of care teams with a new generation of technologies and services. At the same time, Doctolib is helping over 80 million patients to effectively manage their health and provide quick and easy access to optimal healthcare.
Offices: 54, Quai Charles Pasqua, Levallois-Perret, Île-de-France 92300, FR · Mehringdamm, 51, Berlin, Berlin 10961, DE · Via Vittor Pisani 19, Milano, IT · 17, Boulevard de Berlin, Whoorks, Nantes, Pays de la Loire 44000, FR · 362, Avenue de Limoges, Niort, Nouvelle-Aquitaine 79000, FR
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