Associate ML Engineer - Personalization & Recommendations

REA; City of Melbourne; Hybrid; AUD 90,000 - 130,000; Full time

Benefits offered by this job

Hybrid and flexible working

Flexible leave options

Flexible parental leave

Volunteering leave & matched donations

Hackdays

Job summary

REA Group in Melbourne (Richmond) is seeking an Associate Machine Learning Engineer to help build intelligent, personalised property experiences. You’ll work on recommender systems and predictive models powering REA’s web and app platforms, using deep learning, collaborative filtering and content-based methods.

You’ll collaborate with senior ML engineers, contribute to model training, evaluation and deployment, and help maintain AI pipelines across cloud environments, while continuing to grow

Qualifications

• A degree in Computer Science, Data Science, Mathematics, Engineering or a related field.
• Hands-on experience with machine learning, data science or software development.
• Familiarity with Python and ML libraries such as Pandas, NumPy, Scikit-learn or PyTorch.
• Understanding of ML concepts like regression, classification or recommender systems.

Responsibilities

• Design and develop machine learning solutions for REA.
• Build and evaluate ML models including deep learning and recommender systems.
• Develop and deploy ML pipelines for batch and real-time use cases.
• Work with Python, Docker, and cloud platforms (GCP or AWS).
• Collaborate with senior engineers and data scientists to move ideas to production.
• Learn and grow ML skills through hands-on practice and mentoring.

Skills

Python

Machine learning

Data Science

Communication

Education

Degree in Computer Science/Data Science/Mathematics/Engineering

Tools

Pandas

NumPy

Scikit-learn

PyTorch

Job description

REA Group in Melbourne (Richmond) is seeking an Associate Machine Learning Engineer to help build intelligent, personalised property experiences. You’ll work on recommender systems and predictive models powering REA’s web and app platforms, using deep learning, collaborative filtering and content-based methods.

You’ll collaborate with senior ML engineers, contribute to model training, evaluation and deployment, and help maintain AI pipelines across cloud environments, while continuing to grow