ML DevOps Engineer: Cloud, CI/CD & AI Infra

ARM; Galway; Hybrid; EUR 65,000 - 90,000; Full time

Job summary

Arm in Galway, Ireland, is seeking a Machine Learning DevOps specialist to join a team that builds infrastructure and automation for ML software workflows. You will help power cloud enablement, manage shared hardware labs and support engineers with robust CI/CD and containerized environments.

The role emphasizes collaboration with ML teams, infrastructure automation, and practical problem solving across Windows, Linux, MacOs and Android platforms.

Qualifications

• Experience with Linux systems and supporting engineering infrastructure.
• Understanding of DevOps principles and reliable software delivery.
• Ability to write and maintain automation scripts using Bash, Python or similar.
• Experience with CI/CD or containerisation technologies such as Docker or Kubernetes.

Responsibilities

• Partner with ML software teams to understand development and infrastructure needs and support the adoption of DevOps practices.
• Develop and maintain hybrid (Windows, Linux, MacOs, Android) infrastructure, automation and support services for software engineering workflows.
• Support multi-cloud enablement activities and board farm management for ML software development and testing.
• Improve continuous integration and continuous delivery workflows, containerised environments and operational documentation.
• Investigate infrastructure and tooling issues, communicate findings clearly and contribute to practical solutions with the wider team.
• Deploy, monitor and troubleshoot a pool of physical devices (Silicon boards and mobile handsets)

Skills

Linux systems

DevOps principles

Scripting (Bash/Python)

CI/CD concepts

Tools

Docker

Kubernetes

Job description

Arm in Galway, Ireland, is seeking a Machine Learning DevOps specialist to join a team that builds infrastructure and automation for ML software workflows. You will help power cloud enablement, manage shared hardware labs and support engineers with robust CI/CD and containerized environments.

The role emphasizes collaboration with ML teams, infrastructure automation, and practical problem solving across Windows, Linux, MacOs and Android platforms.