Are you passionate about solving complex problems with data and machine learning? Join one of Australia’s leading insurance businesses as they expand their intelligent automation and data science capabilities to drive real business impact.
They are seeking a Machine Learning Engineer to design, build, and deploy ML models that enhance fraud detection, underwriting, claims, and customer experience operations. You'll work alongside actuaries, data scientists, and software engineers in a high-performing and supportive environment.
What You’ll Do

• Design, develop, and deploy scalable ML solutions across key areas like fraud detection, risk modelling, pricing optimisation, and customer insights.
• Collaborate with data scientists to productise ML models and integrate them into business applications.
• Automate data pipelines and model retraining using cloud-native tools (AWS/Azure/GCP).
• Monitor model performance and drive continuous improvement in real-world environments.
• Maintain strong model governance and ensure compliance with data privacy and security standards.
• Contribute to the development of MLOps practices and tools within the business.

What You’ve Got

• 3+ years' experience in a Machine Learning or Data Science role (preferably in financial services or insurance)
• Proficiency in Python and key ML libraries (e.g., scikit-learn, TensorFlow, PyTorch)
• Strong experience with cloud platforms (AWS, Azure, or GCP) and containerisation (Docker, Kubernetes).
• Solid understanding of software engineering best practices, version control (Git), CI/CD pipelines.
• Experience with structured and unstructured data, feature engineering, and model evaluation.
• Ability to communicate complex technical solutions to non-technical stakeholders.
• Bachelor's or Master’s degree in Computer Science, Data Science, Engineering, or related field.

Why Join?

• Work for a well-established Australian brand with a strong focus on digital transformation.
• Be part of a growing Data & AI team with real influence on business strategy.
• Competitive salary, annual bonus scheme, and generous leave entitlements.
• Flexible hybrid work environment (WFH + city-based office).
• Continuous learning opportunities, certifications, and access to cutting-edge tools.

Ready to help reshape the future of insurance with machine learning? Apply now with your CV and a short cover letter outlining your interest.