Senior MLOps Engineer (Full Remote from

Job Title: MLOps Engineer

About
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. Our team of talented individuals from over 40 nationalities embraces four core values every day: Opening perspectives, Building a safer world, Making bold moves, and Creating meaning.
We’re hiring our first dedicated MLOps Engineer. Our ML team runs +100 active AI projects on GCP and needs the industrialized infrastructure to match. The ML team is moving fast, and they need a dedicated expert to connect the dots, align on the right practices, and help both sides deliver at their best. You’ll be that person. You’ll work at the heart of an AI-first environment, where shipping models fast and reliably is the core business, not a side project.

Responsibilities

• 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 ML 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.
• Tackle technical debt on existing projects while laying the right foundations for what’s next.
• Be the technical mediator between ML and Backbone teams; understand both sides, propose solutions that stick.
• Handle run responsibilities: on-call, post-mortems, level-1 failure analysis.

Requirements

• 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).
• AI Coding Assistants (Claude, Cursor, Dust)
• Data lifecycle management (cost, security, encryption)
• Fluent in French and English.