Salary: Up to 100k plus bonus & benefitsOwnership: Take models from research to production and own how AI features run in the real worldImpact: Build machine learning systems used by enterprise customers every dayEnvironment: Product-led AI team solving real problems, not building demosAutonomy: Engineers are trusted to solve problems and ship improvementsYou’ll sit at the centre of the company’s AI delivery, taking work developed by the data science team and turning it into scalable, production-grade systems that power real product features.The RoleThis is a Senior Machine Learning Engineering role focused on productionising AI within a growing SaaS platform. You won’t be training models in isolation.You’ll be responsible for:Turning experiments into reliable systemsEnsuring models perform consistently once deployedBuilding the pipelines and infrastructure that keep everything runningYou’ll work closely with data scientists, product managers and engineering teams to deliver machine learning capabilities that actually reach customers.What You’ll OwnDeployment of ML models from proof-of-concept to productionPerformance optimisation and scalability of deployed modelsInfrastructure and pipelines supporting machine learning systemsMonitoring, evaluation and model health over timeCollaboration with engineering teams to integrate AI features into the productScaling generative AI applications and workflowsWhat You’ll Be DoingMove models from research into production and improve performance, reliability and scalability.MLOps & InfrastructureBuild pipelines and infrastructure to support repeatable model deployment and CI/CD.Generative AI & NLPWork with embeddings, transformers and architectures such as RAG to support product features.MonitoringTrack model performance, accuracy and drift to ensure reliable outputs in production.What You’ll Need5+ years working with machine learning systems in productionExperience deploying ML systems in cloud environments (AWS ideally)Strong experience with Docker and containerised environmentsExperience working with CI/CD pipelines and version-controlled codebasesSolid understanding of machine learning techniques such as classification, regression and clusteringExperience working with NLP models and text-based dataComfortable working in a fast-moving product environmentStrong collaboration with product and engineering teamsNice to HaveExperience with generative AI frameworks such as LangChain or LlamaIndexFamiliarity with RAG architecturesExperience with AWS ML tooling and infrastructure frameworksExposure to analytics or dashboard tools such as PowerBI, Qlik or TableauLocationThis role can be fully remote anywhere in Ireland, hybrid, or office-based depending on your preference.The team meets quarterly in Dublin for in-person collaboration.Please note that visa sponsorship isn’t available, so candidates must already have the right to work in Ireland.Interested?If you enjoy turning AI experiments into real product features and building machine learning systems that operate at scale, this is a role worth exploring. Apply now or mail me out directly
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