AI/ML DevOps Engineer - Cloud & MLOps Expert

Capgemini

Brussel Hoofdstad

Sur place

EUR 70 000 - 110 000

Plein temps

Il y a 30 heures
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Résumé du poste

Capgemini Belgium is seeking a highly skilled DevOps Engineer with AI/ML platform experience to design, implement, and maintain scalable cloud infrastructure supporting AI-driven applications.

The role focuses on CI/CD automation, cloud orchestration, and MLOps practices to enable reliable deployment, monitoring, and cost optimization for AI solutions across AWS, Azure, and GCP. Collaboration with Data Scientists and AI Engineers is essential.

Qualifications

  • 4+ years in DevOps, Cloud Engineering or Site Reliability Engineering.
  • Experience with Azure, AWS or GCP.
  • Infrastructure as Code: Terraform or Ansible.
  • Linux administration, scripting (Python, Bash, PowerShell) and networking basics.
  • Experience deploying and managing AI/ML workloads and MLOps platforms.

Responsabilités

  • Design, implement, and maintain CI/CD pipelines for cloud-native and AI applications.
  • Manage and optimize infrastructure on AWS, Azure, or Google Cloud Platform.
  • Automate deployment, monitoring, and scaling using Infrastructure as Code (Terraform, Ansible, CloudFormation).
  • Support AI/ML model deployment, versioning, and lifecycle management using MLOps practices.
  • Implement containerization and orchestration using Docker and Kubernetes.
  • Monitor system performance, reliability, security, and cost optimization.
  • Collaborate with Data Scientists, AI Engineers, and Software Development teams to operationalize AI solutions.

Connaissances

DevOps
Cloud engineering
SRE
MLOps
AI/ML deployment

Outils

Terraform
Ansible
Docker
Kubernetes

Description du poste

Capgemini Belgium is seeking a highly skilled DevOps Engineer with AI/ML platform experience to design, implement, and maintain scalable cloud infrastructure supporting AI-driven applications.

The role focuses on CI/CD automation, cloud orchestration, and MLOps practices to enable reliable deployment, monitoring, and cost optimization for AI solutions across AWS, Azure, and GCP. Collaboration with Data Scientists and AI Engineers is essential.

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