Senior Machine Learning Engineer

Senior Machine Learning Engineer Cybersecurity Startup | Dublin (Hybrid - 1 day per week) We're partnering with a long-standing cybersecurity startup client in Dublin as they make one of their most important engineering hires to date. Over the past few years, they've built an extensive threat intelligence platform containing tens of millions of vulnerability events, exploit patterns, behavioural signals and threat intelligence data. Now they're looking to make their first dedicated Machine Learning Engineering hire. The Opportunity Most cybersecurity platforms tell customers what has already happened. This team wants to help customers understand what is most likely to happen next. The goal is to build production machine learning systems capable of predicting which vulnerabilities are most likely to be exploited, ranking emerging threats, and helping customers prioritise the risks that matter most. This isn't AI for the sake of AI. It's a genuine engineering challenge built around predictive machine learning, large-scale datasets and solving real customer problems. The Role You'll join an established product engineering team and take ownership of the company's machine learning capability. Working closely with Engineering, Product and R&D, you'll help turn existing proof of concepts into robust production systems while shaping the future direction of machine learning across the platform. You'll be responsible for: Building production machine learning systems Predictive modelling, probability and ranking models Model deployment and inference Monitoring production performance and model drift Retraining and improving models over time Working with large-scale structured and unstructured datasets Collaborating across engineering, product and leadership Helping define the long-term machine learning roadmap This is not a research role. Everything you build will be deployed into production and used directly by customers. What They're Looking For They're looking for someone with genuine experience building and operating production machine learning systems. You'll ideally have experience with: Python Production Machine Learning Predictive Modelling Classification & Ranking Models Model Monitoring Drift Detection & Retraining MLOps & Deployment Pipelines TensorFlow, PyTorch or Scikit-learn Docker, Kubernetes or FastAPI Large-scale structured or unstructured datasets Experience within cybersecurity is a bonus, but absolutely not essential. More important is having experience building machine learning products where the output is a probability, prediction or ranking, rather than simply alerts or detections. Backgrounds in fraud detection, credit risk, recommendation systems, pricing, forecasting or churn prediction would all be highly relevant. Experience with GenAI, LLMs or RAG is welcomed, but this is first and foremost a production machine learning engineering role built around traditional predictive ML. Why Join? First dedicated Machine Learning Engineer Established software engineering team and leadership already in place Significant ownership from day one Influence the future ML direction of the business Large-scale real-world datasets Equity Pension Hybrid working (typically 1 day per week in Dublin) Salary up to €130,000 depending on experience If you've built production machine learning systems and enjoy solving genuinely difficult engineering problems, I'd love to have a chat. How to Apply To apply for this role, submit your CV via the application form provided. Alternatively, to speak in absolute confidence about this opportunity, please contact Jack Tyrrell via Disclaimer If you have a disability which means you require assistance at any stage of the recruitment process, please contact us directly to discuss. We are committed to providing equality of opportunity to all. Please note, we are receiving an exceptionally high number of applications at present and will be unable to shortlist candidates who are not meeting the specific requirements for this role. Due to the high volume of applications, we may be unable to provide individual feedback. We thank you in advance for your understanding. Benefits: Work From Home