Senior ML Ops

# Senior ML Ops (x/f/m)Unlimited ContractEngineeringParis, France## Set a new pulse for healthcareYour mission will be to build and scale the infrastructure that brings machine learning to life at Doctolib

Expérience, qualifications et compétences non techniques, avez-vous tout ce qu'il faut pour réussir dans cette opportunité ? Découvrez-le ci-dessous.
- 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 doYour 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 areBefore 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 .
*.
*## 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 dedicated training## Our interview process
* Recruiter Interview (phone, 45 minutes)
* Hiring Manager Interview (1 hour)
* Case Study & Case Restitution (1 hour)
* Behavioral Interview / Meet the Team (1 hour or half-day immersion)
* At least one reference check
* A copy of your criminal records (