LET’S FIX HOSPITALITY, FOR GOOD.

We’re on a mission to help the hospitality industry double their profitability, reduce their carbon footprint, and create better working environments for their teams.
Our CEO, Conor, founded and scaled Mad Egg - one of the fastest-growing restaurant groups in Ireland. After years of juggling “market-leading” systems, spreadsheets, and paper printouts, he set out to build the solution he wished he had from day one: Nory.
Nory is an all-knowing restaurant management system. It combines real-time data with AI predictive analytics to help restaurants operate with consistency, certainty and profitability. From food prep to forecasting, Nory puts operators in control of their margins.
Now, with demand growing faster than we imagined - and a recent Series A led by Accel - we’re scaling fast. We’ve grown to a team of 50+ across Ireland, the UK and Spain, and we’re just getting started. We’re now looking for a Machine Learning Engineer to join our Data team.

WHAT YOU’LL BE DOING

This role is ideal for a senior independent doer, someone who has owned the entire ML lifecycle and is ready to ship meaningful, production-grade ML systems from scratch. This is not a research or experimentation role; it’s about building systems that work in the real world and move the needle on customer outcomes and business impact.

• Own the end-to-end development of machine learning systems, from business problem formulation and algorithm design through to deployment and monitoring in production
• Collaborate with product managers and engineers to define KPIs, design data flows, and embed algorithms in product features
• Apply best-in-class ML practices with clear problem framing, model evaluation, experimentation, and observability—to deliver real-world impact
• Independently lead the development of models across the platform acting as the primary ML owner and act as the primary ML owner; from data access and cleaning to modelling and integration
• Work autonomously while contributing to a culture of collaboration, shared learning, and continuous improvement
• Actively participate in peer reviews, team rituals, and cross-functional discovery, sharing insight and offering help where needed