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Career Profile

Machine learning engineer

Machine learning engineers design, train and deploy machine learning models, building the pipelines and systems that run them reliably in production.
IT and Digital
Average weekly salary
$2496
Future demand
Strong
Most common education level
Bachelor degree

What does a machine learning engineer do?

A machine learning engineer designs, trains, deploys and maintains machine learning models and the systems that run them. They sit between data science and software engineering, turning experimental models into scalable, production-grade services and building the pipelines that feed and retrain those models. The focus is on model performance, reliability and automation, so that machine learning works dependably in the real world. 

Machine learning engineers work mainly in technology firms, data and AI teams, banks, telecommunications and research organisations, usually in office or hybrid settings. Consulting and professional services firms also employ them to build machine learning solutions for clients.

Is machine learning engineering right for me?

A career as a machine learning engineer may suit you if you enjoy programming, maths and working with data at scale. You need strong software engineering skills, an understanding of machine learning, and the patience to build, test and improve systems.

Adaptability
An ability to manage change positively and perform effectively in changing environments.
Analytical thinking
An ability to analyse and interpret information.
Industry knowledge
A sound awareness and understanding of industry and trends.

Problem-solving and decision-making
The ability to identify issues, evaluate options, and make informed decisions.

Teamwork
An ability to work effectively and collaborate with a range of stakeholders.
Digital and technical capability
Proficiency in using technology, digital tools, and relevant software.

How to become a machine learning engineer

Most machine learning engineers start with a bachelor degree in information technology, computer science or a related field, and build strong skills in programming, data and machine learning. Real projects, through study, personal work or internships, help you develop and show what you can do. Many also go on to postgraduate study. 

Every journey to study is individual, and there are several paths into machine learning engineering. A common path to becoming a machine learning engineer:

  1. Complete a bachelor degree in information technology, computer science or a related field, with study in artificial intelligence and data.
  2. Build strong programming, machine learning and data engineering skills.
  3. Work on real projects that train and deploy models.
  4. Learn tools for pipelines, deployment and cloud platforms.
  5. Consider postgraduate study, and keep learning as the field changes.

Accreditation and qualifications

There is no licence required to work as a machine learning engineer. On the technology pathway, UniSQ's Bachelor of Information Technology is accredited at professional level by the Australian Computer Society (ACS) and recognised internationally through the Seoul Accord.

How long does it take to become a machine learning engineer?

A bachelor degree in information technology or computer science usually takes three years of full-time study, or longer if you study part-time. A major such as Artificial Intelligence and Data Science lets you focus on machine learning and data. 

Building the experience to work as a machine learning engineer usually takes further practice on real projects, and many complete postgraduate study. Many people move into the role after starting in software development or data. 

Start your journey with UniSQ

Build the technical foundation for a machine learning career with a UniSQ information technology degree, where you can major in Artificial Intelligence and Data Science. 

Bachelor of Information Technology
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Responsibilities and work settings

Day-to-day responsibilities

Training and validating machine learning models.

Building and automating data and training pipelines.

Deploying and scaling models in production.

Monitoring model accuracy and retraining as needed.

Working with data scientists, engineers and product teams.

Where you might work

Accounting, consulting and professional services firms

Banks and financial institutions

Cloud computing and IT infrastructure organisations

Data analytics and artificial intelligence organisations

Research institutes and research centres

Software development and technology companies

Telecommunications providers

Machine learning engineer FAQs

Pay for machine learning engineers varies with experience, employer and specialisation.

Most machine learning engineers hold a bachelor degree in information technology, computer science or a related field, with strong programming and machine learning skills. Many also complete postgraduate study. There is no single mandatory qualification, so practical projects and technical skill matter alongside your degree.

Data scientists focus more on exploring data and building models, while machine learning engineers focus on turning those models into reliable, scalable systems in production. The roles overlap, and many machine learning engineers come from a software engineering background.

Machine learning engineering is a fast-growing, in-demand area of technology. It suits people who enjoy programming, data and building systems. A UniSQ information technology degree with a major in Artificial Intelligence and Data Science provides the foundation to enter the field.

Day to day, a machine learning engineer might train and test a model, build a data pipeline, deploy a model to production, monitor its accuracy, and work with data scientists and developers. The role combines machine learning with software engineering.

Related careers

Data scientist
Data analyst

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Disclaimer: UniSQ’s Career Finder is a guide only. While reasonable care is taken to ensure accuracy, career information may change over time. Career statistics are sourced from Your Career and Jobs and Skills Australia. © Commonwealth of Australia. Licensed under CC BY 4.0. Salary figures listed on this page are in Australian Dollars (AUD).