Machine Learning Engineer

Machine Learning Engineer

Location: Hybrid – Dublin

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.

Key Responsibilities:

End-to-End ML Ownership

• Own ML solutions from problem definition → data preparation → modeling → deployment → monitoring → iteration
• Design and implement training pipelines, evaluation frameworks, and inference systems
• Collaborate closely with product, data, and backend engineering teams to deliver real-world impact

NLP & Model Development

• 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

MLOps & Production Systems

• 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

Data Engineering & Integration

• 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

Engineering Excellence & Infrastructure

• 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)

Requirements:

Experience & Seniority

• 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

Strong ML Engineering Skills

• 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)

NLP & Transformers

• 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

MLOps & Infrastructure

• 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)

Data & Systems Integration

• 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*

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

Email: [email protected]

Phone: (090) 6450 760