Senior DevOps Engineer (Full Remote from France)
- Role
- DevOps
- Experience
- Senior
- Employment
- Full-time
- Company size
- Mid-size
Open to FR only. Set where you work from to check your eligibility.
No BS summary
Senior DevOps/MLOps engineer based in France, fluent in French and English. Must be strong with GCP, Kubernetes, GitOps, MLOps tooling, GPU infrastructure, Python/Bash, Terraform, Docker/Helm, and observability.
Core skills
Required skills
Optional skills
Required languages
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
We're hiring our first dedicated Devops / MLOps Engineer
Our ML team runs +100 active AI projects on GCP and needs the industrialized infrastructure to match. 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.
Your Mission
- 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, 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 Backbone teams understand both sides, propose solutions that stick.
- Handle run responsibilities: on-call, post-mortems, level-1 failure analysis.
What We're Looking For
- 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.
Nice to Have
- Jupyter Notebooks, broader ML/AI ecosystem
- Data pipelines (Airflow, Dataflow, Kestra)
- 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.
Don't check every box? Apply anyway.
We're looking for the right person, not the perfect resume. If this role excites you, let's talk.
Dailymotion is an equal opportunity employer. All positions are open to people with disabilities. Need accommodations? Just let us know.
🗓️ Interview Process
- HR Interview with Marvin (30mn)
- Manager interview with Cédric & Thierry (1h)
- Technical Interview with 2 Architects (1h) : no coding test, just a real technical conversation.
- ML Interview with Brice & Samuel (1h)
- Final Interview with Alan, VP Platform (1h)
Welcome at Dailymotion 🎉
What you'll do
- 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, 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 Backbone teams understand both sides, propose solutions that stick.
- Handle run responsibilities: on-call, post-mortems, level-1 failure analysis.
What they require
- 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.
- 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.
- You lead by example: you advocate for best practices by winning people over, not by imposing them.
Benefits
- Don't check every box? Apply anyway.
- All positions are open to people with disabilities.
- Need accommodations? Just let us know.
- Technical Interview with 2 Architects (1h) : no coding test, just a real technical conversation.
Dailymotion c'est plus qu’une app vidéo, c’est une conversation visuelle en mouvement qui repose sur un algorithme unique pensé pour développer l'esprit critique des utilisateurs. Dailymotion Pro est une solution d'hébergement et de diffusion vidéo pour les professionnels, et Dailymotion Advertising est une plateforme vidéo marketing propriétaire.