Machine Learning Engineer

We are seeking a hands‑on Machine Learning Engineer to design, build, and deploy production‑grade AI systems, with a strong focus on NLP and modern transformer‑based models.

This role goes beyond model development—you will own end‑to‑end ML systems, from problem formulation and data pipelines to deployment, monitoring, and continuous improvement. You’ll play a key role in embedding AI into mission‑critical systems (e.g., healthcare platforms), ensuring solutions are scalable, reliable, and compliant.

This is an ideal role for someone who combines deep ML expertise (especially NLP/LLMs) with strong MLOps and software engineering skills.

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• Design and implement training pipelines, evaluation frameworks, and inference systems
  
• Collaborate closely with product, data, and backend engineering teams to deliver real‑world impact
  
• Build and optimize NLP systems using transformer architectures (e.g., BERT, encoder–decoder, decoder‑only models)
  
• Fine‑tune and adapt pretrained language models for domain‑specific use cases
  
• Evaluate model performance, trade‑offs, and metrics for NLP tasks
  
• * (Bonus) Work with large‑scale models using GPU clusters, data/model parallelism, or quantization techniques
  

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• Build and maintain CI/CD pipelines for ML systems
  
• Deploy models as scalable APIs and microservices
  
• Monitor model performance, data drift, and system health in production
  
• Implement robust versioning, testing, and rollback strategies
  
• Develop and optimize ETL pipelines and data workflows (e.g., healthcare formats like FHIR/HL7 where applicable)
  
• Build and maintain feature stores and data layers for training/serving consistency
  
• Integrate ML outputs into production systems alongside backend teams
  

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• Write clean, maintainable, production‑grade Python code
  
• Use Docker and Kubernetes to orchestrate ML workloads
  
• Work with cloud platforms (AWS, Azure, or GCP) for scalable infrastructure
  
• Ensure systems meet security, privacy, and compliance standards (e.g., regulated environments like healthcare)
  

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• 4+ years of professional experience in machine learning, data engineering, or software engineering
  
• Proven track record of hands‑on coding and system building (not just leadership or oversight)
  
• Experience working on production ML systems, not only research or prototypes
  
• Advanced Python proficiency (primary language)
  
• Experience with ML frameworks such as PyTorch or TensorFlow
  
• Ability to build training pipelines, evaluation workflows, and inference systems
  
• Experience with production‑grade engineering (testing, scalability, deployment)
  

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• Hands‑on experience with transformer models (e.g., BERT, RoBERTa, encoder–decoder, decoder‑only)
  
• Experience fine‑tuning pretrained models
  
• Strong understanding of NLP evaluation metrics and performance trade‑offs
  

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• Experience building ML pipelines and CI/CD workflows
  
• Hands‑on experience with tools like Airflow, Prefect, Kubeflow, or similar
  
• Experience deploying models using Docker and Kubernetes
  
• Familiarity with cloud platforms (AWS, Azure, or GCP)
  

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• Experience with data processing tools (Pandas, Spark, dbt, SQL)
  
• Ability to build and maintain data pipelines and feature stores
  
• Experience integrating ML into production applications or APIs
  

Applicants must be eligible to work in Ireland without the need for future sponsorship.