Kubernetes & Distributed Systems Engineer (Benchmarking)

remote work

United States

Remote

USD 90,000 - 140,000

Full time

14 days+

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Job summary

Logos (λ) is building a sovereign, people-owned technology stack to revitalise civil society and protect digital liberties at scale. This role, part of the Institute of Free Technology Technical Services, focuses on evaluating performance and reliability of Logos and other IFT projects.

You will design and optimize Kubernetes clusters for large-scale experiments, improve scalability, and collaborate with researchers to ensure reproducible results.

Qualifications

  • Strong experience with Kubernetes and container orchestration.
  • Solid understanding of cloud infrastructure, Linux, and networking.
  • Familiarity with monitoring tools like Grafana and Prometheus.
  • Infrastructure as code experience with Terraform, Ansible or Helm.
  • Proficiency in Python.
  • Interest in distributed systems, P2P networks, or blockchain.

Responsibilities

  • Design, configure, and optimize Kubernetes clusters for large-scale experiments.
  • Improve cluster scalability and resource utilization for complex deployments.
  • Set up, maintain, and optimize monitoring, logging, and observability stacks.
  • Collaborate with researchers to streamline experimentation workflows.
  • Automate infrastructure and deployment workflows for reliability.
  • Troubleshoot and tune distributed workloads for accurate benchmarking.

Skills

Kubernetes
Cloud infrastructure
Linux systems
Networking
Distributed systems
Python
Docker

Tools

Grafana
Prometheus
VictoriaLogs
Terraform
Ansible
Helm

Job description

Logos (λ) is building a sovereign, people-owned technology stack to revitalise civil society and protect digital liberties at scale. This role, part of the Institute of Free Technology Technical Services, focuses on evaluating performance and reliability of Logos and other IFT projects.

You will design and optimize Kubernetes clusters for large-scale experiments, improve scalability, and collaborate with researchers to ensure reproducible results.

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