Set a new pulse for healthcare!

We are looking for a Senior MLOps Engineer to join the ML Platform team.

Your mission will be to build and scale the infrastructure that brings machine learning to life at Doctolib — powering AI-driven solutions that improve the daily experience of care teams and patients across Europe. You will work in a cross-functional team developing the ML platform and tooling that underpins Doctolib's AI products, contributing directly to faster, more reliable deployment of models that have a real impact on healthcare delivery.

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 do

Your responsibilities include but are not limited to:

Build and deploy production-grade machine learning models in close collaboration with data scientists and engineers, ensuring performance, scalability, and reliability
Design and maintain the MLOps pipeline, including version control, CI/CD, and monitoring of ML models in production
Develop tools, frameworks, and best practices to streamline the model development and deployment lifecycle
Ensure the availability and performance of ML systems, proactively identifying and resolving issues before they impact users
Partner with cross-functional teams to gather requirements, provide technical guidance, and contribute to the development of end-to-end ML solutions
Share and advocate MLOps knowledge across the tech community, documenting processes, standards, and best practices to drive consistency and knowledge transfer

Who you are

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:

Are proficient in Python, SQL, Shell Scripting, and Terraform, with hands-on experience building and containerizing ML pipelines with Docker
Have solid knowledge of cloud platforms, particularly AWS services such as SageMaker, EC2, ECS, S3, and CloudWatch (and/or Azure equivalents)
Have a good understanding of machine learning algorithms, concepts, and trends, including hands-on experience with Deep Learning frameworks — preferably PyTorch
Have excellent communication and collaboration skills, with the ability to work effectively in cross-functional teams and produce clear technical documentation
Have a strong team spirit, a genuine enthusiasm for learning, and a proactive sense of initiative
Are fluent in English

It would be fantastic if you:

Have experience with Kubernetes, GitOps tools (e.g. ArgoCD), and/or Kafka
Have experience with ML model quantization, optimization, and HuggingFace technologies (Transformers, Accelerate, PEFT)
Have experience with JavaScript/TypeScript and browser-based model deployment (transformers.js / langchain.js)

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 we offer

Free comprehensive health insurance (basic package) 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
ParentCare Program: Enjoy full salary coverage (100%) during your first month of birth leave and 75% during the second, covered by Doctolib
Enrollment in Doctolib's long-term employee value sharing plan called DoctoGrowth
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

Senior ML Ops (x/f/m) at Doctolib