Principal Machine Learning Engineer

Advanced Resource Managers Ltd; Dublin; On-site; EUR 120,000 - 180,000; Full time

Job summary

Advanced Resource Managers Ltd is seeking a Principal Machine Learning Engineer to lead the evolution of a large-scale AI and ML platform, guiding architecture, deployment, and operation of both traditional ML systems and agentic AI solutions.

This is a hands-on leadership role for someone who still codes but also defines strategy, sets standards, and mentors engineers to ensure secure, scalable, observable, and production-ready AI.

Qualifications

• 8+ years of hands-on engineering experience in ML/Platform/MLOps in enterprise environments.
• Strong Python expertise and production ML shipping track record.
• Deep Azure experience; AWS considered as alternative.
• Proficient in Terraform, Docker/Kubernetes, CI/CD, and IaC.

Responsibilities

• Define and lead architecture for ML and agentic AI platforms.
• Design and own MLOps and LLMOps across production environments.
• Build CI/CD, IaC, deployment automation, and platform reliability standards.
• Lead agent-to-agent communication and orchestration frameworks.
• Drive Azure-based AI infrastructure decisions and platform evolution.
• Mentor engineers and act as senior escalation point for production issues.

Skills

Python

Azure

MLOps

LLMOps

Observability

Multi-agent systems

Agentic AI

Production support

Tools

Docker

Kubernetes

Terraform

CI/CD

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.