Senior Machine Learning Engineer

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.

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.

• 
  
• 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
  

Move models from research into production and improve performance, reliability and scalability.

Build pipelines and infrastructure to support repeatable model deployment and CI/CD.

Work with embeddings, transformers and architectures such as RAG to support product features.

Track model performance, accuracy and drift to ensure reliable outputs in production.

• 
  
• 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
  

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

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.

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