ML / AI Jobs in Ireland
There are 74 open ML / AI jobs in Ireland on freehire right now. 7 of them were posted recently. The skills employers ask for most often are machine-learning, ai and python.
Most requested skills
- machine-learning 97%
- ai 82%
- python 70%
- pytorch 42%
- llm 41%
- cloud 39%
- tensorflow 34%
- deep-learning 31%
How the work is done
- Remote 14 · 19%
- Hybrid 9 · 12%
- Onsite 3 · 4%
Visa sponsorship offered in 50% of the 14 postings that state a position on it.
Seniority
- Senior 18
- Lead 16
- Staff 13
- Principal 5
Who is hiring
- 1000+ employees 23
- 501-1000 employees 9
- 11-50 employees 3
- 51-200 employees 1
Lead, Finance Analytics & Enablement AI/ML
Lead a team to build and optimize finance analytics, AI/ML automation, and GCP infrastructure for a travel-tech startup, turning financial data into actionable insights.
Lead, Finance Analytics & Enablement AI/ML
Lead finance analytics and AI enablement at a travel-tech startup, building data pipelines, optimizing GCP costs, and deploying LLM-based systems to automate financial reporting and decision-making.
Lead Machine Learning Engineer
Lead the design and deployment of AI/ML models for document understanding, using NLP and computer vision to automate contract analysis and improve customer experiences on Docusign’s platform.
Staff Machine Learning Engineer
Build and deploy production-grade machine learning systems for ad-targeting and analytics using Databricks, MLFlow, and cloud infrastructure.
Machine Learning Platform Engineer
Build and operate ML infrastructure, design training and inference systems, and optimize model serving for performance and scalability.
Machine Learning Platform Engineer
Build and operate the ML infrastructure powering an AI assistant, focusing on model training, deployment, inference, and observability to enable reliable, scalable, and cost-efficient production systems.
Staff ML Engineer: Edge AI for Self-Healing Vehicles
Lead ML engineering for edge AI that monitors vehicle health in real time, building pipelines to train and deploy models on constrained in-vehicle devices.
Principal AI/ML Scientist – Engineer
Lead a team of AI/ML scientists and engineers to build agentic workflows and reasoning engines for Pipedrive’s AI-native CRM, shipping production-grade models that drive customer value from structured and unstructured data.
Staff ML Engineer — Edge AI for Self-Aware Vehicles
Lead edge AI development for in-vehicle health monitoring and prediction, optimizing ML models for embedded hardware and deploying them on resource-constrained devices.
Graduate ML/AI Engineer
Build and deploy ML and generative AI models for manufacturing use cases like predictive maintenance and quality control, working with Python, PyTorch, and RAG pipelines in a hybrid Limerick role.
Senior ML Engineer (AI Research/ Portability)
Build and evaluate AI agent architectures that work reliably across different models, providers, and environments, focusing on portability, interoperability, and optimization.
AI/ML Computational Scientist - GenAI & MLOps
Design and deploy enterprise AI solutions, integrating custom models with cloud AI services and building scalable MLOps pipelines for training and production.
Machine Learning Engineer
Build and optimize large-scale data pipelines and integrate LLMs into production systems for Docusign’s Intelligent Agreement Management platform.
Lead AI/ML Engineer - Enterprise Platform Solutions
Lead AI/ML engineering for agentic and LLM-powered workflows that enhance enterprise platforms and boost productivity at JPMorganChase.
AI/ML Computational Scientist
Design and deploy AI/ML solutions for enterprise clients, including custom models, GenAI/LLMs, and scalable MLOps pipelines in cloud environments.
Lead AI/ML Solutions Architect
Designs and builds scalable AI/ML systems for enterprise clients, including data pipelines and deep learning models deployed across cloud, edge, and HPC environments.
AI/ML Solutions Scientist: GenAI & Production Pipelines
Design and deploy GenAI and ML solutions for enterprise clients, building scalable MLOps pipelines and tailoring LLMs to business needs.