Jobs / Doctolib
Senior ML Ops (x/f/m)
Doctolib · Levallois-Perret, A8, France
Levallois-Perret, A8, FranceRemote
Remuneration
Health insurance, paid vacation and RTT, mental health and coaching services, work-from-abroad flexibility, lunch vouchers, sports or creative activity subsidy, public transport reimbursement, birth leave salary coverage, employee value sharing plan, caregiver and disability support, relocation support, and AI tools and training.
Location
Levallois-Perret, A8, France
Visa sponsorship
Not specified
Job summary
The Senior MLOps Engineer builds and scales the infrastructure, platform, and tooling that bring machine learning models into production for healthcare products serving care teams and patients. The role covers model deployment, MLOps pipelines for version control, CI/CD, and monitoring, and the reliability of production ML systems, in collaboration with data scientists and engineers. The stated stack includes Python, PySpark, SQL, AWS SageMaker, Terraform, and Docker.
Benefits
Health insurance for employee and children25 days of paid vacation and up to 14 days of RTTMental health and coaching servicesLunch vouchersSports or creative activity subsidy50% public transport subscription reimbursementBirth leave salary coverageLong-term employee value sharing planCaregiver and disability supportRelocation supportAI tools and dedicated training
Qualifications
- Proficiency in Python, SQL, shell scripting, and Terraform.
- Hands-on experience building and containerizing ML pipelines with Docker.
- Knowledge of AWS services, including SageMaker, EC2, ECS, S3, and CloudWatch, or equivalent Azure services.
- Understanding of machine learning algorithms and concepts, with hands-on deep learning framework experience, preferably PyTorch.
- Strong communication, collaboration, and technical documentation skills.
- Fluency in English.
Responsibilities
- Build and deploy production-grade machine learning models.
- Design and maintain MLOps pipelines for version control, CI/CD, and production monitoring.
- Develop tools, frameworks, and practices to streamline model development and deployment.
- Maintain the availability and performance of production ML systems and resolve issues proactively.
- Gather requirements and provide technical guidance for end-to-end ML solutions.
- Document and share MLOps processes, standards, and best practices.
Skills
Argo CDAWSAzureBashCloudWatchDockerECSJavaJavaScriptKafkaKotlinKubernetesPythonS3TerraformTypeScriptRuby
Languages
English
Work schedule
Full-time
Travel
Work from abroad for up to 10 days per year
Industry
Healthcare
Security clearance
Copy of criminal records (French extrait de casier judiciaire B3) required durin
Relocation
Yes