Senior ML Ops (x/f/m)

Doctolib
Paris, France
On-site

Who this role is best for

A natural match if you have experience building and deploying ML models in healthcare.

Best fit for

  • Candidates with a background in deploying AI solutions for healthcare stakeholders
    — “powering AI-driven solutions that improve the daily experience of care teams and patients across Europe”
  • Individuals who have led MLOps pipelines in production environments with cloud platforms
    — “Design and maintain the MLOps pipeline, including version control, CI/CD, and monitoring of ML models in production”
  • Professionals adept at containerizing and scaling ML systems using Docker and Terraform
    — “proficient in Python, SQL, Shell Scripting, and Terraform, with hands-on experience building and containerizing ML pipelines with Docker”

Things to consider

  • The role requires a high level of English fluency and may involve international collaboration
    — “Are fluent in English”
  • Candidates must be prepared to provide a criminal records extract as part of the process
    — “A copy of your criminal records (extrait de casier judiciaire B3)”

How to stand out

  • Highlight cross-functional impact and documentation of ML deployment processes
    — “Share and advocate MLOps knowledge across the tech community, documenting processes, standards, and best practices to drive consistency and knowledge transfer”
  • Demonstrate experience with model optimization and HuggingFace technologies
    — “Have experience with ML model quantization, optimization, and HuggingFace technologies (Transformers, Accelerate, PEFT)”
  • Emphasize your ability to identify and resolve ML system issues proactively
    — “Ensure the availability and performance of ML systems, proactively identifying and resolving issues before they impact users”
Pace · Fast PacedCollaboration · HighAutonomy · MediumDecision Impact · Team

Derived from job-description analysis by Serendipath's career intelligence engine.

What success looks like

  • build and deploy production-grade ML models
  • design and maintain MLOps pipeline
  • develop tools and frameworks
  • ensure ML system availability
  • partner with cross-functional teams
Typical background
professional experience in MLOpsacademic or personal projects involving ML deployment

Skills & requirements

Required

MlopsPythonSQLShell ScriptingTerraformDockerCloud PlatformsAWS ServicesMachine Learning AlgorithmsDeep Learning FrameworksCommunication And CollaborationTechnical Documentation

Preferred

KubernetesGitops ToolsML Model QuantizationHuggingface TechnologiesJavascript/typescriptBrowser-based Model Deployment

Stack & domain

PythonSQLShell ScriptingTerraformDockerAWSSagemakerEC2ECSS3CloudwatchKubernetesGitopsArgocdKafkaML Model QuantizationOptimizationHuggingfaceTransformersAcceleratePEFTJavaScriptTypeScriptBrowser-based Model DeploymentTransformers.jsLangchain.jsCommunicationCollaborationTeam SpiritEnthusiasm For LearningProactive InitiativeMlopsAI In HealthcareCloud PlatformsMachine Learning AlgorithmsDeep Learning FrameworksAI Ethics

About the role

Original posting from Doctolib via Greenhouse

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 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 (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

We welcome everyone

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 privacy

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.

Source: Doctolib careers (Greenhouse)

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