ML Ops Engineer
Paris, FranceFull-TimeMid-levelAI / Data Science
How you’ll make an impact
- Design, implement and maintain ML pipelines and CI/CD workflows (training, deployment, retraining)
- Expose ML models through inference APIs (Cloud Run / Vertex AI Endpoints) to be consumed by product and platform services
- Own monitoring, alerting and reliability of ML systems in production
- Write optimized, high-performance, scalable, testable, maintainable, and observable code
- Ensure operational readiness of ML models (logging, metrics, incident handling)
- Act as a local ML Ops reference for the Paris Data Science team
- Support DS teams to industrialize models and experiments
Collaboration
- Work in an international, multi-brand environment with teams across Europe, Canada, and the US
- Collaborate with platform teams (Canada/US) on GCP infrastructure and standards
- Work closely with Product squads of E&E brands to understand and address their needs
- Collaborate with Data Engineers and software architect to ensure data quality and production deployment of models
- Promote a data-driven culture in a highly collaborative environment and share your expertise
Technology watch
- Stay up to date with advances in machine learning and devops to apply best practices within the company
We could be a match if
- You hold an engineering degree or a Master’s degree in mathematics or computer science, with at least 5–6 years of experience in similar roles
- You enjoy discovering scientific methods and challenging existing ones, always keeping in mind the ultimate goal of improving the performance of our dating application
- Experience with ML / DevOps practices
- Experience with CI/CD, Docker, Terraform
- Experience with monitoring & alerting (Cloud Monitoring, Grafana, etc.)
- Understanding of IAM, service accounts, security
- Comfortable operating ML systems in production
- Strong understanding of model serving constraints
- Comfortable communicating in English during meetings
- Excellent analytical and synthesis skills
- Excellent written and verbal communication skills
- Rigorous scientific mindset
- Team spirit and proactive attitude
- Curiosity and strong learning ability
Nice to have
- Experience working with Kafka or event-driven architectures in ML or data platforms
- Knowledge in A/B test framework
- Knowledge in QlikView, Looker, or other BI tools
