Senior MLOps Engineer (Full Remote from France)

• Empower ML Engineers with the tools, infrastructure, and frameworks they need to iterate fast autonomously.
• Accelerate time-to-market for production-ready ML products: seamless integration, proper service connections, access to data and resources.
• Own ML CI/CD in close collaboration with the DevExp team, adapting existing frameworks to ML-specific needs, not just consuming them.
• Keep ML Engineers in control of their models in production: monitor, troubleshoot, iterate, refine directly in prod, no staging/prod mirror.
• Enable large-scale ML experimentation: robust, reproducible, scalable environments for both internal tests and A/B testing in production.
• Deliver concrete MLOps building blocks (MLflow, Kubeflow, KubeRay...) and manage GPU infrastructure dynamically, you've seen L40 shortages mid-training, you know how to handle them.
• Tackle technical debt on existing projects while laying the right foundations for what's next.
• Be the technical mediator between ML and DevExp: understand both sides, propose solutions that stick.
• Handle run responsibilities: on-call, post-mortems, level-1 failure analysis., * Jupyter Notebooks, broader ML/AI ecosystem
• AI Coding Assistants (Claude, Cursor, Dust)
• Data pipelines (Airflow, Dataflow, Kestra)
• Data lifecycle management (cost, security, encryption)
• Redis clusters and infrastructure performance optimization

What Will Make the Difference

Beyond the tech stack, what will set you apart is your ability to act as a bridge rather than a silo. You thrive in ambiguity, stay calm under pressure, and turn complexity into clear solutions. You have a run culture, post-mortems and on-call sharpen you rather than drain you. And you lead by example: you advocate for best practices by winning people over, not by imposing them.

• Solid MLOps or DevOps, background projects shipped in prod matter more than years on a resume.
• GCP expert: Vertex AI, GKE, GCS, BigQuery.
• Full GitOps: FluxCD first, ArgoCD accepted.
• Kubernetes in prod, not just in a lab.
• Hands-on with real MLOps tools: MLflow, Kubeflow, KubeRay.
• GPU-aware: you've managed GPU scarcity at scale during mass training runs.
• Python is a must, Bash expected, Go or Rust a plus.
• IaC (Terraform), containerization (Docker, Helm), observability (Prometheus, Datadog, Looker).
• Fluent in French and English.

Dailymotion is more than a video app, it's a visual conversation in motion, based on a unique algorithm designed to broaden users' horizons. Dailymotion brings nuance to the debates that animate young people and puts listening, discovery, and kindness back at the heart of interactions to help build a better and safer Internet. Dailymotion is also "Dailymotion Pro", a video hosting and broadcasting solution for professionals in all sectors; and "Dailymotion Advertising", a powerful, proprietary video advertising platform, offering a high-quality, secure environment for brands. Our team is made up of 400 people in France, New York, and Singapore, all united by the same ambition: to visibly shake up the global video platform ecosystem. What brings us together? At Dailymotion, our team of talented individuals from over 40 nationalities embraces four core values every day: * Opening perspectives - We are building bridges between different sides of the spectrum. We believe in freedom of speech, inclusivity, and a mix of cultures. * Building a safer world - Empathy is the key to understanding alterity. Caring for each other is our driver to creating a safe community. * Making bold moves - We are ambitious challengers. We are making against-the-flow choices to make visible changes in the platform's ecosystem * Creating meaning - We spark joy and curiosity, we feel good about what we do and we want everyone else to feel the same fulfillment