Salary: Up to 100k plus bonus & benefits
Ownership: Take models from research to production and own how AI features run in the real world
Impact: Build machine learning systems used by enterprise customers every day
Environment: Product-led AI team solving real problems, not building demos
Autonomy: Engineers are trusted to solve problems and ship improvements
You’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 Role
This 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 systems
Ensuring models perform consistently once deployed
Building the pipelines and infrastructure that keep everything running
You’ll work closely with data scientists, product managers and engineering teams to deliver machine learning capabilities that actually reach customers.
What You’ll Own
Deployment of ML models from proof‑of‑concept to production
Performance optimisation and scalability of deployed models
Infrastructure and pipelines supporting machine learning systems
Monitoring, evaluation and model health over time
Collaboration with engineering teams to integrate AI features into the product
Scaling generative AI applications and workflows
What You’ll Be Doing
Move models from research into production and improve performance, reliability and scalability.
MLOps & Infrastructure
Build pipelines and infrastructure to support repeatable model deployment and CI/CD.
Generative AI & NLP
Work with embeddings, transformers and architectures such as RAG to support product features.
Monitoring
Track model performance, accuracy and drift to ensure reliable outputs in production.
What You’ll Need
5+ years working with machine learning systems in production
Experience deploying ML systems in cloud environments (AWS ideally)
Strong experience with Docker and containerised environments
Experience working with CI/CD pipelines and version‑controlled codebases
Solid understanding of machine learning techniques such as classification, regression and clustering
Experience working with NLP models and text‑based data
Comfortable working in a fast‑moving product environment
Strong collaboration with product and engineering teams
Nice to Have
Experience with generative AI frameworks such as LangChain or LlamaIndex
Familiarity with RAG architectures
Experience with AWS ML tooling and infrastructure frameworks
Exposure to analytics or dashboard tools such as PowerBI, Qlik or Tableau
Location
This 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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