Senior/Principal Machine Learning Engineer - Aus

About Your Role

Reporting to the Head of AI Engineering, the Senior/Principal ML Engineer translates the latest advances in artificial intelligence, including foundation models and self-supervised learning, into AI-as-a-medical-device products. Our AI Engineers work in dynamic teams alongside Software Developers, Testers, Cloud DevOps and Integration Engineers. We're looking for a self-starter whose passion for learning shows in the adoption of new tools and best practice. As part of our Rç team, we offer the unique opportunity to make a direct, meaningful impact on the lives of patients and their families.

What You'll Do:

• Develop AI algorithms, prototypes and solutions for healthcare, with a focus on foundation models and self-supervised learning;
• Optimise models and training pipelines for accuracy, scale and rapid experimentation;
• Follow agile methodology and software engineering best practice, focussing on test-driven development, rapid prototyping, validation and iteration;
• Provide regular technical and other progress reports relevant to projects, and ensure all progression is properly documented;
• Engage with the literature to benchmark against and adopt state-of-the-art techniques and algorithms;
• Rigorously evaluate generative AI models, and partner closely with teams training models at scale; and
• Contribute to a culture of excellence, helping to solve problems as they arise, instil a culture of best practice, integrity and agility, as well as champion the Harrison mission internally and externally.

What You'll Bring:

• Extensive experience in an ML engineering or applied research role, working closely with software development teams;
• Extensive experience with Python and modern deep learning frameworks such as PyTorch;
• Hands-on experience building foundation models and self-supervised learning methods;
• Honours or higher academic qualification in computer science, and/or strong quantitative grounding and equivalent software engineering work experience; and
• Experience evaluating generative AI models and partnering with model training at scale.

Nice to have skills and characteristics

• Experience with healthcare data and solutions;
• Practical experience in building, deploying and testing ML models in a product development context using software engineering best practices;
• Experience with large-scale distributed training, AWS cloud development, and/or computer vision and natural language processing;
• Experience with a range of AI tools and techniques;
• PhD in ML or equivalent research experience; and
• Publications or open-source contributions in foundation models, self-supervised learning or generative AI.

Why join us?

Innovate for Global Good. Join us to pioneer world first AI technology that transforms patient outcomes and helps build a healthier, fairer world.

Collaboration Across Continents. Work with brilliant minds from every corner of the globe in a culture built on trust, autonomy, and genuine teamwork.

Well Funded & Global. Backed by world class investors including Aware Super, Blackbird Ventures, Skip Capital, and Horizons Ventures, we've raised over US$240M to accelerate our global impact.

Scale Your Potential. Tap into yearly L&D budgets, mentoring, hackathons, and secondments-all supported by a transparent growth framework to grow your career.

Flex for Life. Work when and where you do your best-with WFH options, flexible hours, and the autonomy to make an impact your way.

Support for Every Family Journey. From fertility to parenthood, loss, and even grandparenthood-we provide inclusive, thoughtful policies to support families in every stage.

We are proud to be an Equal Opportunity Employer. Diversity's not a buzzword here, it's in our DNA. Diverse perspectives shape our culture and make our work better. We're committed to building inclusive teams that represent a variety of backgrounds and skills. We look forward to hearing from you.