Principal Machine Learning Engineer (Contract)

Ocho People Ltd.; Dublin; Hybrid; EUR 166,000 - 277,000; Part time

Benefits offered by this job

Hybrid working

Job summary

Ocho People Ltd. is seeking a Principal Machine Learning Engineer for a 6‑month contract in Dublin. Hybrid schedule requires about 2 days on site weekly, with the rest remote. You will own architectural decisions for an agent estate, guiding both ML models and agentic services in production.

You will mentor a Senior ML Engineer, define CI/CD standards, and evaluate Azure/AWS infra with data science leadership. Strong Azure or AWS experience is essential.

Qualifications

• 8+ years in machine learning or platform engineering with ownership of production systems.
• Experience building AI infrastructure at scale on Azure or AWS.
• Experience with ML and agentic/LLM systems in the same estate.

Responsibilities

• Own end-to-end architecture of the agent estate including build, deploy and monitoring.
• Set standards for CI/CD, env management and release processes across models and services.
• Design platform use of MCP servers and A2A communication for reliable orchestration.
• Establish production observability, evaluation and drift detection for ML systems.
• Lead integration of new components with legacy data sources.
• Act as senior technical authority on Azure or AWS AI infra and evaluate Azure Foundry.
• Mentor the Senior ML Engineer and set direction across engineering.
• Represent feasibility, cost and risk in architecture decisions with DS leadership.
• Serve as escalation point for production infrastructure issues.

Skills

Python

Azure

AWS

MLOps

LLMOps

Agent framework

CI/CD

Terraform

SQL

Azure/AWS infra

Tools

Docker

Podman

Terraform

CI/CD pipelines

Job description

Principal Machine Learning Engineer (Contract)

At a Glance

• Principal level contract: 6 months, with extension possible
• Azure (preferred) or AWS, MCP, A2A, MLOps and LLMOps
• Hybrid, around 2 days a week on site in Dublin (NI commuters welcome)
• Extremely competitive day rate
• Set the technical direction for an agent estate running in production

About the Company

Our client is an established insurance business based in Dublin, investing seriously in agentic AI alongside a mature conventional machine learning estate. The programme is delivered in partnership with one of the world's largest IT services and consulting providers, bringing global AI expertise and tooling to the work. It's a rare chance to shape a modern agent platform inside a regulated enterprise, where engineering decisions carry real weight.

The Role

This is the senior engineering seat on the programme. You'll own the architecture of the agent estate, from how agents and conventional ML models are built and deployed to how they're observed and kept reliable in production. You'll pair closely with the data science leadership on shared priorities and mentor the Senior Machine Learning Engineer. It suits a principal or staff engineer who still writes code, has carried production systems through real incidents, and is just as comfortable setting long term technical direction.

Key Responsibilities

• Own the end to end architecture of the agent estate, covering build, deployment, monitoring and reliability
• Set the standards and reusable patterns for CI/CD, environment management and release processes across ML models and agentic services
• Design how the platform uses MCP servers and A2A agent to agent communication, so agents can be composed, discovered and orchestrated reliably
• Establish production observability and evaluation practices for LLM based and conventional ML systems, including monitoring, alerting, drift detection and rollback
• Lead the integration of new agentic components with legacy services and existing data sources
• Act as the senior technical authority on Azure or AWS AI infrastructure, including evaluation of Azure AI Foundry
• Mentor the Senior Machine Learning Engineer and set technical direction across the wider engineering function
• Represent engineering feasibility, cost and risk in architectural decisions made jointly with data science leadership
• Serve as the escalation point when a production issue needs deep infrastructure expertise

What You'll Need

Essential:

• 8+ years in machine learning or platform engineering, with hands on ownership of production systems
• Proven experience building AI infrastructure at scale on Azure (strongly preferred) or AWS
• Experience running conventional ML models and agentic or LLM systems side by side in the same estate
• A track record of greenfield delivery integrated with legacy services and data sources
• Python at senior or architect level
• Docker or Podman, Terraform, and ownership of CI/CD pipeline design in an ML context
• SQL and database management
• MCP server development and A2A (Agent2Agent protocol), or deep agent to agent and tool orchestration experience you can map onto them quickly
• MLOps and LLMOps, including production observability and evaluation
• Experience with at least one agent framework or SDK
• Eligible to work in Ireland and able to be in the Dublin office around 2 days a week

Desirable / Nice to Have:

• Azure AI Foundry experience
• RAG systems and vector stores such as pgvector or Pinecone
• ETL and DAG orchestration tooling, or serverless architectures

Why Apply?

• Extremely competitive day rate
• 6 month contract with extension possible
• Hybrid working, around 2 days a week on site in Dublin, with NI commuters welcome
• Set the technical direction for a greenfield agentic platform
• Put the newest agent standards, MCP and A2A, to work in a real production estate
• Genuine influence, with an equal voice alongside data science leadership on architecture