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Doctolib is seeking a Senior MLOps Engineer to join the ML Platform team. Your mission is 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.
Key Responsibilities:
- 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
Doctolib's tech stack includes Rails, TypeScript, Java, Python, Kotlin, Swift, and React Native. The company leverages AI ethically across its products to empower patients and health professionals. The role is permanent, full-time, with a hybrid work setup (up to 2 remote days per week) and an immediate start date.
Requirements:
- Proficiency in Python, SQL, Shell Scripting, and Terraform
- Hands-on experience building and containerizing ML pipelines with Docker
- Solid knowledge of cloud platforms, particularly AWS services such as SageMaker, EC2, ECS, S3, and CloudWatch (or Azure equivalents)
- Good understanding of machine learning algorithms, concepts, and trends, including hands-on experience with Deep Learning frameworks (preferably PyTorch)
- Excellent communication and collaboration skills, with the ability to work effectively in cross-functional teams and produce clear technical documentation
- Strong team spirit, genuine enthusiasm for learning, and proactive sense of initiative
- Fluency in English
Nice-to-Have:
- Experience with Kubernetes, GitOps tools (e.g., ArgoCD), and/or Kafka
- Experience with ML model quantization, optimization, and HuggingFace technologies (Transformers, Accelerate, PEFT)
- Experience with JavaScript/TypeScript and browser-based model deployment (transformers.js / langchain.js)
