Senior ML Engineer — Production‑Ready Predictive Models (Hybrid)

MCS Group; Leinster; Hybrid; EUR 111,000 - 148,000; Part time

Job summary

MCS Group is seeking a Senior Machine Learning Engineer / ML Specialist for a day-rate contract in Ireland. This 12-week initial engagement is hybrid, with an immediate start.

You will be a senior, hands-on contractor to assess and improve predictive models based on historical vulnerability and threat data, aiming for production-ready delivery. You will work autonomously, progressing from data exploration to deployment, monitoring, and retraining, with strong focus on traditional ML rather than

Qualifications

• Strong Python and production ML experience.
• Background in classification, predictive modelling, risk/probability scoring, anomaly detection or time-series modelling.
• Experience taking models from data and experimentation through to deployment, monitoring, drift and retraining.
• Comfortable working independently in an ambiguous environment, without a large ML team around you.
• Experience in a start-up, scale-up, consultancy or small ML team would be advantageous.

Responsibilities

• Assess and improve existing predictive models built around historical vulnerability and threat data.
• Move work toward reliable, production-ready solutions.
• Work autonomously to understand data and models and decide next steps.

Skills

Python

Production ML

Classification

Predictive modelling

Risk scoring

Anomaly detection

Time-series modelling

Model deployment

Monitoring

Drift monitoring

Job description

MCS Group is seeking a Senior Machine Learning Engineer / ML Specialist for a day-rate contract in Ireland. This 12-week initial engagement is hybrid, with an immediate start.

You will be a senior, hands-on contractor to assess and improve predictive models based on historical vulnerability and threat data, aiming for production-ready delivery. You will work autonomously, progressing from data exploration to deployment, monitoring, and retraining, with strong focus on traditional ML rather than