Job Overview & Organization Mission

Develop personalization algorithms, automated property valuation models, and computer vision tools that guide millions of Australian home buyers at REA Group.

REA Group’s Personalization & AI team is hiring an experienced Machine Learning Engineer. Working at our Richmond tech hub, you will build and deploy end-to-end ML pipelines that deliver hyper-personalized property recommendations, predict market price movements, and classify real estate photography at scale.

As a key member of the team at REA Group in Melbourne, VIC, you will play a central role in driving excellence, upholding top-tier Australian industry standards, and contributing directly to the strategic milestones of one of the nation’s premier employers.

Key Duties & Core Responsibilities

In this critical role, your operational duties and key performance responsibilities will encompass:

• Design, train,: Design, train, and deploy deep learning and collaborative filtering recommendation models in production.
• Build automated: Build automated MLOps pipelines using MLflow, Kubeflow, and AWS SageMaker.
• Implement feature: Implement feature stores and low-latency real-time inference endpoints for mobile and web clients.
• Conduct rigorous: Conduct rigorous online A/B testing, offline model evaluation, and fairness audits.
• Collaborate with: Collaborate with data engineers and product managers to extract value from petabytes of property telemetry.

Required Qualifications, Licenses & Experience

To be successful in this position at REA Group, candidates are expected to satisfy the following essential selection criteria:

• Mandatory Qualification: Master’s or Bachelor’s in Machine Learning, Computer Science, Data Science or Statistics.
• Relevant Experience: Minimum 4+ Years of verified industry experience in Australia or recognized overseas equivalence.
• 4+ years of experience training and deploying machine learning models into production systems.
• Deep proficiency with Python, PyTorch / TensorFlow, and scientific computing stacks (NumPy, pandas).
• Demonstrated experience with recommendation systems, ranking algorithms, or computer vision.
• Solid software engineering fundamentals including version control, CI/CD, and Docker containerization.

Core Competencies & Key Technical Proficiencies

The successful applicant will possess demonstrated capabilities across the following domain skill sets:

Salary, Compensation & Employee Benefits

At REA Group, we understand that our people drive our achievements. An outstanding remuneration and wellbeing package is provided in line with Australian benchmarks:

• Competitive Remuneration: AU$155,000 – AU$185,000 per year + standard Australian Superannuation (11.5%).
• Compensation $155,000 – $185,000 + annual incentive bonus.
• Flexible hybrid work policy with Richmond office featuring wellbeing studios and game rooms.
• Generous learning budget for international AI conferences, research papers, and compute credits.
• Leave Entitlements: 4 weeks annual leave (with 17.5% annual leave loading where applicable) plus 10 days paid personal/carer’s leave.
• Flexible Work: Progressive work-life balance options with supportive corporate culture and leadership development pathways.

About the Employer: REA Group

REA Group operates realestate.com.au, delivering world-class property search, advertising, and financing tools across Australia.

REA Group is deeply committed to building diverse, equitable, and culturally inclusive work environments. We proudly celebrate diversity and welcome applications from all qualified individuals including First Nations Australians, people with disabilities, and candidates from culturally and linguistically diverse backgrounds.

Application Process & Next Steps

Applications for this position are currently open and being reviewed on a rolling basis. Suitable candidates are encouraged to apply as early as possible before the published closing date.

Please prepare an updated Curriculum Vitae (CV) and a tailored Cover Letter highlighting your relevant experience against the key selection criteria outlined above.

To proceed with your application, click the Apply on Employer Site button to access the official REA Group careers gateway.