Senior Machine Learning Engineer

We’re a leading business management solution with a core purpose: helping more businesses in Australia and New Zealand start, survive and succeed.

At MYOB, we believe what’s good for one business is good for all business—and for all of us. Whether you support them, work for them, or dream of building your own, when businesses run smoothly, everybody feels it. Owners, employees, customers, suppliers—even families. That’s why we’re here: to give every person in business the tools they need to focus on what really matters and do Big Things—whatever big looks like for them.

And for you? Joining MYOB means being part of that impact. It means using your skills to help businesses thrive, shaping the future of work, and growing alongside the people and communities we support. Because while we’re the business of software, we’re really in the business of people. And that makes MYOB Everyone’s Business.

Are you a forward-thinking Machine Learning Engineer prepared to develop powerful AI solutions that redefine how businesses operate? At MYOB, we empower small businesses with transformative technology.

Be part of our Data & AI Team to develop and broaden applications with MYOB’s product ecosystem and data to compose AI-powered experiences for SMEs and Enterprises, enhancing efficiency and confidence.

As a foundational member of the AI team, you’ll shape the technical vision and build systems that directly impact our customers' success. This is a unique opportunity to:

- Design and implement machine learning systems from the ground up, with a focus on large language models (LLMs) and foundation models tailored to small business needs.

- Develop and deploy AI-powered features for automated document understanding, financial forecasting, and conversational interfaces.

- Optimise AI systems for scalability, safety, and reliability on AWS infrastructure.

- Work in a dynamic, zero-to-one environment, bringing ideas from concept to production.

- Build from Scratch: Develop and optimise machine learning systems, focusing on innovative solutions for small business accounting challenges.

- Deploy at Scale: Create scalable workflows to train, deploy, and monitor machine learning models on AWS services like SageMaker and Bedrock.

- End-to-End Ownership: Lead projects from ideation to production, implementing MLOps guidelines for robust and efficient solutions.

- Collaborate and Innovate: Work with product managers, engineers, and collaborators to align technical solutions with customer and business goals.

- Technical Expertise: Proficiency in machine learning frameworks (e.g., TensorFlow, PyTorch) and experience with LLMs and foundation models (e.g., GPT, Claude, Llama).

- Cloud-Native Experience: Solid understanding of AWS services (SageMaker, Bedrock, S3) and cloud-based architectures.

- MLOps Skills: Expertise in CI/CD pipelines for ML, model versioning, monitoring, and containerisation (Docker, Kubernetes).

- Customer Focus: Passion for solving real-world challenges for small businesses through innovative AI applications.

- Innovation: Excels in uncertain settings, showcasing ingenuity and perseverance to construct influential systems from scratch.

- Bachelor’s or Master’s degree in Computer Science, Data Science, Machine Learning, or a related field.

- Relevant certifications (e.g., AWS Certified Machine Learning – Specialty) are highly desirable.