Senior DevOps Engineer (MLOps)

TL;DR

Senior DevOps Engineer (MLOps): Building and industrializing infrastructure for over 100 active AI projects on GCP with an accent on MLOps frameworks and GPU resource management. Focus on accelerating time-to-market for ML products, implementing robust CI/CD pipelines, and ensuring scalable experimentation environments.

Location: Remote (Must be based in France)

Salary: EUR 75,000 - 85,000 yearly

Company

hirify.global is a global video platform and professional broadcasting solution focused on building a safer and more inclusive Internet.

What you will do

• Empower ML Engineers with necessary tools, infrastructure, and frameworks for autonomous iteration.
• Accelerate time-to-market for production ML products via seamless integration and resource access.
• Own and adapt ML CI/CD pipelines in close collaboration with the ML team.
• Implement MLOps building blocks including MLflow, Kubeflow, and KubeRay.
• Manage GPU infrastructure dynamically to handle scarcity during large-scale training.
• Act as a technical mediator between ML and Backbone teams to align on best practices.

Requirements

• Strong background in DevOps/MLOps with proven experience shipping projects to production.
• Expertise in GCP (Vertex AI, GKE, GCS, BigQuery).
• Proficiency in Kubernetes and GitOps (FluxCD or ArgoCD).
• Hands-on experience with MLflow, Kubeflow, and KubeRay.
• Strong Python skills; Bash, Go, or Rust are highly valued.
• Fluent in French and English.

Nice to have

• Experience with Jupyter Notebooks and the broader ML/AI ecosystem.
• Knowledge of data pipelines (Airflow, Dataflow, Kestra).
• Experience with Redis clusters and infrastructure performance optimization.

Culture & Benefits

• Permanent full-time contract.
• Work in an AI-first environment with a global team.
• Culture of inclusivity, empathy, and bold moves.
• Full remote flexibility within France.

Hiring process

• HR Interview (30 min).
• Manager interview (1 hour).
• Technical Interview with two Architects (1 hour).
• ML Interview (1 hour).
• Final Interview with VP Platform (1 hour).