Principal Machine Learning Engineer

Arm; Dublin; On-site; EUR 120,000 - 180,000; Full time

Job summary

Arm seeks a Principal Machine Learning Engineer to lead a large-scale AI platform, shaping architecture, deployment, and operation of conventional ML systems and agentic AI solutions. This hands-on leadership role combines coding with strategic direction across an expanding engineering function.

You will own the platform roadmap, set engineering best practices, and ensure AI systems are secure, scalable, observable, and production-ready.

Qualifications

• 8+ years' experience in Machine Learning Engineering, Platform Engineering, MLOps, or AI Infrastructure.
• Strong Python expertise and a track record of shipping production ML systems.
• Deep Azure experience (AWS also considered).
• Hands-on experience with agentic AI, multi-agent systems, MCP, A2A, or similar orchestration frameworks.
• Experience working within enterprise environments where integration with existing systems is critical.

Responsibilities

• Define and lead the architecture for ML and agentic AI platforms.
• Design and own MLOps and LLMOps practices across production environments.
• Build standards for CI/CD, Infrastructure as Code, deployment automation, and platform reliability.
• Lead the implementation of agent-to-agent communication and orchestration frameworks.
• Drive Azure-based AI infrastructure decisions and platform evolution.
• Integrate modern AI capabilities with complex enterprise and legacy systems.
• Mentor engineers and act as the senior escalation point for platform and production issues.

Skills

Python

Azure

MLOps

LLMOps

Observability

CI/CD

IaC

Multi-agent

Agentic AI

Production ML

Architecture

Tools

Terraform

Docker

Kubernetes

Job description

We're seeking a Principal Machine Learning Engineer to lead the evolution of a large-scale AI and machine learning platform, driving the architecture, deployment, and operation of both conventional ML systems and next-generation agentic AI solutions.

This is a hands-on leadership role for someone who still enjoys coding but can also define technical strategy, make architecture decisions, and provide direction across a growing engineering function. You'll own the platform roadmap, establish engineering best practices, and ensure AI systems are secure, scalable, observable, and production-ready.

What you'll be doing

• Define and lead the architecture for ML and agentic AI platforms.
• Design and own MLOps and LLMOps practices across production environments.
• Build standards for CI/CD, Infrastructure as Code, deployment automation, and platform reliability.
• Lead the implementation of agent-to-agent communication and orchestration frameworks.
• Drive Azure-based AI infrastructure decisions and platform evolution.
• Integrate modern AI capabilities with complex enterprise and legacy systems.
• Mentor engineers and act as the senior escalation point for platform and production issues.

What we're looking for

• 8+ years' experience in Machine Learning Engineering, Platform Engineering, MLOps, or AI Infrastructure.
• Strong Python expertise and a track record of shipping production ML systems.
• Deep Azure experience (AWS also considered).
• Strong knowledge of Terraform, Docker/Kubernetes, CI/CD, and Infrastructure as Code.
• Experience with MLOps, LLMOps, observability, monitoring, and production support.
• Hands-on experience with agentic AI, multi-agent systems, MCP, A2A, or similar orchestration frameworks.
• Experience working within enterprise environments where integration with existing systems is critical.

This is an excellent opportunity for a Staff or Principal-level engineer who wants to shape the future of enterprise AI while remaining close to the technology.