Machine Learning Engineer | Hybrid – Dublin

We’re looking for a Machine Learning Engineer to help power AI within Healthcare Information Systems. This role is ideal for someone who enjoys building production-ready ML systems — not just models, but the infrastructure that makes them reliable, scalable, and secure in the real world.

If you’re passionate about MLOps, cloud infrastructure, and production stability, this could be a great fit.

Responsibilities:

MLOps & Deployment

• Build and maintain CI/CD pipelines for ML (testing, deployment, version control)
• Deploy models as scalable APIs and microservices
• Monitor model performance, data drift, and system health in production

Data Engineering & Integration

• Develop and optimise ETL pipelines for healthcare data (FHIR, HL7)
• Support feature stores and data layers to ensure training/production consistency
• Integrate ML outputs into core healthcare applications alongside backend teams

Engineering Excellence

• Write clean, maintainable Python code
• Use Docker & Kubernetes to orchestrate ML workloads
• Ensure systems meet strict security and compliance standards (HIPAA/HITRUST)

Requirements:

• 3–5 years’ experience in software or data engineering
• At least 2 years working with ML in production environments
• Strong Python skills (SQL required; Go or Java a bonus)
• Experience with AWS, Azure, or GCP
• Hands-on experience with Docker
• Familiarity with ML frameworks (PyTorch or Scikit-learn)
• Experience with MLOps tools (Airflow, Prefect, Kubeflow, etc.)
• Experience with data tools such as Pandas, Spark, or dbt

Desired:

• Experience deploying Large Language Models (LLMs)
• Background in a regulated industry (Healthcare, Finance, etc.)
• Knowledge of APIs and microservices architecture

For more information or to apply, please contact: Aoife Regan

Email: [email protected]

Phone: (090) 6450 760)