The Role
Build and scale ML platform infrastructure, deploy production machine learning models, and maintain MLOps pipelines with version control, CI/CD, monitoring, and reliability practices. Develop tools and frameworks that streamline model deployment, collaborate with data scientists and engineers on end-to-end AI solutions, resolve production issues, and document and promote MLOps best practices across the technology organization.
Summary Generated by Built In
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 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
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)
- 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 dedicated training
- 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 (extrait de casier judiciaire B3)
We want your experience to be clear, respectful, and transparent. Learn more about our hiring process on our candidate experience page.
Job details- Permanent position
- Tech stack: Python, PySpark, SQL, AWS SageMaker, Terraform, Docker
- Full-time
- Paris, France
- Hybrid work setup (up to 2 remote days per 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!
Your data privacyAll 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.
Skills Required
- Proficiency in Python, SQL, Shell Scripting, and Terraform
- Hands-on experience building and containerizing machine learning pipelines with Docker
- Solid knowledge of cloud platforms, particularly AWS services such as SageMaker, EC2, ECS, S3, and CloudWatch, or Azure equivalents
- Understanding of machine learning algorithms, concepts, and trends
- Hands-on experience with deep learning frameworks, preferably PyTorch
- Excellent communication and collaboration skills
- Ability to produce clear technical documentation
- Fluency in English
- Experience with Kubernetes, GitOps tools such as ArgoCD, and/or Kafka
- Experience with ML model quantization and optimization
- Experience with Hugging Face Transformers, Accelerate, or PEFT
- Experience with JavaScript or TypeScript and browser-based model deployment using transformers.js or langchain.js
Am I A Good Fit?
Get Personalized Job Insights.
Our AI-powered fit analysis compares your resume with a job listing so you know if your skills & experience align.
Success! Refresh the page to see how your skills align with this role.
The Company
What We Do
Since Doctolib's creation in 2013, we have had one purpose: strive for a healthier world. 1. We aim to improve the daily lives of care teams by providing them with a new generation of technologies and services. 2. We aim to improve health for all, by offering a fast and frictionless journey for all care episodes, creating new ways for people to receive care and empowering them to become actors of their health. At Doctolib, we are honored to work in the healthcare field and we believe that innovation in healthcare should be handled differently. We apply 4 guiding principles in everything we do: 1. We create helpful solutions for care teams and people. 2. We serve everyone equally and create well-designed and accessible technologies. 3. We team up with our users to strive for a healthier world and act as one team. 4. We protect our users' privacy. It’s their health, their data. To achieve our purpose, we are assembling a team dedicated to improving healthcare, with a human-centric approach and an entrepreneurial mindset. www.doctolib.com
