Senior Machine Learning Engineer

Collins McNicholas Group; Dublin; Hybrid; EUR 120,000 - 170,000; Full time

Benefits offered by this job

Competitive salary

25 days AL

Pension

Life assurance

Healthcare

Employee discounts

Global Recognition program

Hybrid working

Job summary

Collins McNicholas Group in Dublin seeks a Senior Machine Learning Engineer to join a leading global healthcare company. The role is full-time, permanent, and hybrid, offering opportunities to build scalable ML systems and collaborate across disciplines.

Responsibilities include translating business needs into technical requirements, deploying DL/LLM models, and ensuring data privacy with GDPR/HIPAA compliance. Strong cloud and CI/CD expertise are valued.

Qualifications

• Master’s/PhD in computer science, mathematics, or related fields, or a Bachelor’s with 5+ years in ML.
• 5+ years of experience in a machine learning engineering role or related field.
• Experience building end-to-end ML/AI pipelines (data ingestion to deployment).

Responsibilities

• Collaborate with domain experts, data scientists, and stakeholders to translate business requirements into technical specs.
• Build automated pipelines for data processing and training, evaluation and deployment of deep learning or LLM models including Agentic AI.
• Design scalable infrastructure for model training and inference, in cloud and on-premises.
• Set up monitoring to enable proactive countermeasures for model degradation.
• Ensure data privacy and GDPR/HIPAA compliance during development and deployment.

Skills

Machine Learning

Interdisciplinary collaboration

Education

Master's/PhD in CS/Math or related

Bachelor’s with 5+ years in ML

Tools

Docker

Kubernetes

Git

CI/CD

Job description

Senior Machine Learning Engineer
Our client, a leading global healthcare company are looking for a Senior Machine Learning Engineer to join their team in Dublin. This is a full time, permanent hybrid role. As a Senior Machine Learning Engineer, you will have the opportunity to tap into your curiosity and collaborate with some of the most innovative and diverse people around the world.

Responsibilities:

• Collaborating cross-functionally with domain experts, data scientists, and stakeholders to translate business requirements to technical requirements
• Implementing automated pipelines for data processing and the training, evaluation and deployment of deep learning or LLM models including Agentic AI
• Designing scalable infrastructure for model training and inference, both in the cloud and on-premises
• Setting up monitoring to enable the implementation proactive countermeasures for model degradation
• Enabling data privacy and compliance with healthcare regulations such as GDPR and HIPAA during model development and deployment.

Requirements:

• Master's degree or PhD in computer science, mathematics, OR related fields or Bachelor’s degree with at least 5 years of experience
• 5 years + experience in a machine learning engineering role or related field
• Experience creating engineering solutions that support an AI / ML model’s lifecycle including data ingestion, training, evaluation, and deployment
• Familiarity with a cloud provider, preferably AWS
• Proficiency in large-scale data processing technologies, such as Hadoop and Spark
• Hands-on experience with scalable model deployment, e.g., using Docker and Kubernetes
• Capability of providing maintainable and reusable code including source control with Git, unit and integration testing and a solid knowledge of CI/CD concepts
• Solid understanding of Machine Learning methods
• Familiarity with the integration of LLMs and Agentic AI into real-world software solutions, for example via MCP
• Demonstrated ability of working in interdisciplinary environments

Benefits:

• Competitive salary
• 25 days AL
• Pension
• Life assurance
• Healthcare
• Employee discounts
• Global Recognition program
• Hybrid working