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Wallet icon Coin icon Rate 7 000 € - 9 000 € / month info
Timer icon Form of cooperation Full-time
Briefcase icon Sector Telco
Location icon Location 100% Remote

info The reward is calculated upon delivery of 20 MD per month (1MD=8h)

Project duration 8-20 months with the possibility of extension
Period of cooperation 01.05.2026 - 31.12.2026
Start date ASAP or by agreement
Technology
  • UNIX/Linux
  • Kubernetes
  • Ansible
  • Terraform
  • Helm
Languages
  • English flag English - active, B2/C1/C2

Project description

  • design, implementation, and operation of a Kubernetes platform for AI workloads
  • management and development of bare-metal infrastructure and Kubernetes clusters
  • design and operation of the NVIDIA AI software stack (e.g., Slurm, Run:AI)
  • management and development of container orchestration and deployment processes
  • implementation and management of CI/CD pipelines (Jenkins, GitLab)
  • implementation and management of GitOps processes
  • automation of deployments and infrastructure (Helm, Ansible, Terraform)
  • troubleshooting, performance tuning, and scaling of Kubernetes workloads
  • management of container images and registries (Docker, Podman, scanning – Trivy)
  • integration and management of object storage and persistent volumes
  • implementation of monitoring and observability (Prometheus, Grafana)
  • support and operation of AI and HPC workloads
  • collaboration with infrastructure and AI teams in delivering solutions
  • adherence to ITIL processes

Project requirements

  • min. 5+ years of project experience as a Platform Engineer and/or Architect
     
  • experience with:
    • operating Kubernetes clusters in production (CKA or equivalent)
    • CI/CD tools (Jenkins, GitLab) and GitOps approach
    • Helm and Kubernetes resource management
    • scripting (Python, Bash)
    • Infrastructure as a Code (Terraform, Ansible)
    • container technologies (Docker, Podman)
    • monitoring (Prometheus, Grafana)
    • operating and scaling distributed systems
    • AI / GPU cloud platform and NVIDIA infrastructure
       
  • experience with the following is a big advantage:
    • NVIDIA AI stack (Slurm, Run:AI)
    • large-scale AI / HPC workloads
    • object storage and persistent storage solutions
    • image security and scanning (Trivy)
    • bare-metal Kubernetes environments
    • data engineering / data pipeline tools
       
  • advantage: CKS (Certified Kubernetes Security Specialist) certification
     
  • analytical and technical thinking
  • proactive approach and focus on automation
  • ability to solve complex technical problems
  • team collaboration and effective communication
  • emphasis on quality, stability, and performance
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