Working Life

Machine Learning (ML) Engineers build smart AI systems that study data to find hidden patterns and trends. These advanced systems then make independent decisions and predictions without humans needing to program every step.

They work with large amounts of data, write and test computer code, and improve machine learning models to make sure they are accurate, reliable, and useful in real-world situations. They also help monitor and update AI systems after they are deployed to ensure they continue to perform effectively.

About Machine Learning Engineering 

Machine learning engineering is a part of artificial intelligence (AI) that involves teaching computers to learn from information, find patterns, and make decisions without being told exactly what to do every time.

A good example of machine learning in action is self-driving cars. These vehicles use cameras, sensors, and AI systems to collect and analyse information about the road, helping them understand their surroundings and make safe decisions.

Typical tasks of a Machine Learning Engineer

• Collect and prepare data by cleaning, organising, and processing information so it can be used by AI systems.
• Build and train machine learning models that can identify patterns, make predictions, and improve from data.
• Write and test computer code to develop reliable AI solutions and machine learning applications.
• Evaluate and improve AI models by testing accuracy, performance, and reliability.
• Put machine learning systems into use in real-world applications and ensure they work effectively.
• Monitor and update AI models to maintain performance as new data becomes available.
• Work with data scientists, software engineers, and business teams to develop practical AI solutions for real-world problems.

Machine Learning (ML) Engineers work in the following areas:

• Technology: Developing AI software, cloud-based systems, automation solutions, recommendation tools, and smart digital products.
• Finance: Building AI models to detect fraud, assess risks, improve customer services, and support data-driven financial decisions.
• Healthcare: Creating AI systems that support medical research, medical image analysis, diagnosis, personalised treatment, and healthcare data management.
• Pharmaceuticals and Life Sciences: Using machine learning to analyse scientific data, support drug discovery, improve clinical research, and help develop new medicines.
• Cybersecurity: Developing intelligent systems that detect unusual activity, identify cyber threats, and protect digital services and networks.
• Research and Innovation: Working with universities, research centres, and industry teams to develop new AI methods, test emerging technologies, and solve complex problems.
• Manufacturing and Engineering: Using AI for automation, quality control, predictive maintenance, and improving production processes.
• Energy and Sustainability: Developing AI solutions to improve energy efficiency, manage renewable energy systems, and analyse environmental data.
• Retail and E-commerce: Building recommendation systems, customer analytics tools, and demand forecasting models.
• Public Services: Supporting government organisations and public services through data analysis, automation, and improved digital solutions.

Career opportunities

There is a growing need for machine learning engineers in many areas, including technology, finance, healthcare, pharmaceuticals, cybersecurity, and automotive industries.

Cities such as Dublin, Galway, and Cork are important technology hubs, with global companies, startups, and research organisations looking for people with AI skills.

Employers value skills in programming languages such as Python, data analysis, machine learning tools, cloud technology, statistics, and software development. Knowledge of ethical AI, data protection, and managing large amounts of data can also help improve career opportunities.

This occupation is typically suited for people with the following Career Interests:

 Investigative

The Investigative person will usually find a particular area of science to be of interest. They are inclined toward intellectual and analytical activities and enjoy observation and theory. They may prefer thought to action, and enjoy the challenge of solving problems with sophiscticated technology. These types prefer mentally stimulating environments and often pay close attention to developments in their chosen field.

 Realist

Realists are usually interested in 'things' - such as buildings, mechanics, equipment, tools, electronics etc. Their primary focus is dealing with these - as in building, fixing, operating or designing them. Involvement in these areas leads to high manual skills, or a fine aptitude for practical design - as found in the various forms of engineering.

Realists like to find practical solutions to problems using tools, technology and skilled work. Realists usually prefer to be active in their work environment, often do most of their work alone, and enjoy taking decisive action with a minimum amount of discussion and paperwork.

 Administrative

Administrative people are interested in work that offers security and a sense of being part of a larger process. They may be at their most productive under supervisors who give clear guidelines and while performing routine tasks in a methodical and reliable way.

They tend to enjoy clerical and most forms of office work, where they perform essential administrative duties. They often form the backbone of large and small organisations alike. They may enjoy being in charge of office filing systems, and using computers and other office equipment to keep things running smoothly. They usually like routine work hours and prefer comfortable indoor workplaces.

To become a machine learning engineer in Ireland, you need recognised qualifications, practical experience, and strong technical skills.

Typical qualifications include:

• Masters degree or PhD in a relevant field
• Undergraduate degree in computer science, engineering or mathematics
• Experience in computer programming is essential

Key certifications include:

• QQI Level 8 & 9 qualifications in AI, Applied Computing, or Machine Learning
• SOLAS courses in software development with data analytics modules
• Certified Data Science and AI Programs under the National Framework of Qualifications (NFQ)

Education and Training Entry Routes:

QQI Level 8 and Level 9 qualifications:
Degrees, higher diplomas, and postgraduate courses in areas such as computer science, artificial intelligence, data science, software engineering, and machine learning.

• TU Dublin: Provides a BSc in Computing with Machine Learning & Artificial Intelligence (TU862) and a Data Science and AI (TU850) degree for undergraduates. 

Further Education and Training (FET) courses:
Programmes offered through Education and Training Boards (ETBs) and supported by SOLAS can provide entry routes into technology careers, including areas such as software development, data analytics, and AI skills.

SOLAS also supports AI-focused micro-qualifications through the Skills to Advance initiative.

Springboard+ courses:
Government-supported courses that allow eligible learners to upskill or change careers in areas such as computing, data analytics, and artificial intelligence. The Irish government funds many free and low-cost part-time programs, such as the Certificate in AI and Machine Learning Engineering at South East Technological University.

Computer science and engineering degrees:
Many machine learning engineers begin with a degree in computer science, software engineering, mathematics, statistics, physics, or a related subject before specialising in AI.

Postgraduate conversion courses:
Graduates from other fields can move into AI through higher diplomas or masters programmes focused on computing, data analytics, or artificial intelligence.

• University of Limerick: Offers an MSc in Artificial Intelligence and Machine Learning, teaching neural networks and data mining.
• University College Cork: Features an MSc in Mathematical Modelling and Machine Learning, focusing on the math behind algorithms.
• National College of Ireland: Runs an MSc in Artificial Intelligence to teach the complete lifecycle of AI software.

Industry certifications and online learning:
Professional certifications in cloud computing, data science, programming, and AI tools can strengthen job applications when combined with practical projects.

Work experience and projects: Building a portfolio of machine learning projects, contributing to open-source work, completing internships, or gaining experience in software development and data analysis can help develop the skills employers look for.

Salary Range (thousands per year)* €75k - €110k

Salaries vary by employer, role, location, and duties.

Data Source(s):
Indeed/Morgan McKinley/Payscale/UCD

Last Updated: July, 2026