Machine Learning Built MLOps Trained NLP Models

Are you interested in building software that creates meaningful social impact? Every solution this company develops is deployed directly to production, delivering tangible, real‑world benefits within the healthcare sector.

This Irish software company develops AI‑driven services using large language models, combining in‑house components (30%) with third‑party AI APIs and platforms (70%), including Cursor integrated with Claude models. While AI can be simple and intuitive on its own, this role involves working with a sophisticated AI system that introduces technical complexity and encourages innovative problem‑solving.

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• Essential skill set with strong experience in model development and training – building custom models, implementing data pipelines, and fine‑tuning pretrained models.
  
• Machine Learning & Frameworks: PyTorch (3+ years).
  
• Experience deploying GPU models in production, including concurrent (high‑request) models.
  
• Transformer‑based NLP models (2+ years commercial experience); must have trained NLP models and practiced using the Hugging Face Transformers library.
  
• Familiarity with BERT (advantage).
  
• Production deployment (2+ years) – experience deploying Transformer/NLP models (e.g., Hugging Face, BERT) in a production environment.
  
• MLOps & Deployment – designed & built MLOps pipelines, understanding of model versioning, experiment tracking, CI/CD for ML, and automated CI/CD pipelines (e.g., GitHub Actions) with deployment and scaling using Docker.
  
• Third‑party LLM integration (1+ year) – integrating LLMs via APIs in production environments.
  
• Backend & Cloud expertise – proficient in Python for backend services and ML pipelines; experience with FastAPI, Flask, or similar; hands‑on commercial experience with cloud ML platforms such as AWS Bedrock, Google Vertex‑AI, or Azure OpenAI.
  
• Nice to have: agentic domain, ASR, LLM fine‑tuning and deployment, building and deploying RAG systems in production, real‑time systems and low‑latency optimisation.
  

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• NLP API Development & Maintenance (Approx 40%) – delivering new features (80%) and handling ongoing maintenance and improvements (20%).
  
• MLOps (Approx 20%) – designing and maintaining data pipelines, automating deployment workflows, and managing model versioning.
  
• ASR Model Fine‑Tuning (Approx 15%) – fine‑tuning ASR models to improve accuracy and performance.
  
• LLM Fine‑Tuning for ASR (Approx 15%) – adapting and fine‑tuning large language models for ASR‑related tasks. xcfaprz
  
• R&D and Experimentation (Approx 20%) – research, experimentation, and prototyping for fine‑tuning LLMs and training NLP models.
  

Location: Dublin City Centre, hybrid

Rachel Kelly IT Recruitment Limited

Senior (5+ years of experience)

Tagged as: Industry, Ireland, Language Modeling, Machine Learning, NLP