Machine Learning Engineer / Data Scientist at The Argyle Network

Apply for Machine Learning Engineer / Data Scientist at The Argyle Network in Sydney, NSW, AU. This Full time on site position offers great opportunities for career growth.

Machine Learning Engineer / Data Scientist Build. Shape. Lead. The company’s first Machine Learning hire. This is a rare opportunity for a Machine Learning Engineer / Data Scientist to take the lead in building something truly new — my client's first dedicated ML capability within its growing Registry business.

You’ll join at an exciting inflection point, where technology and financial data intersect, and where machine learning can transform how insights are created, decisions are made, and value is delivered. This person will have the freedom to set the technical direction, choose the tools, and shape the strategy for how ML and AI are embedded across the platform — working in a team that values creativity, experimentation, and tangible outcomes over bureaucracy.

What You’ll Do

• Lead the ML journey – own end-to-end projects from concept through to production deployment and monitoring.
• Build smart systems – develop models for anomaly detection, forecasting, and data quality improvement that directly impact how the business operates.
• Engineer solid foundations – design scalable data pipelines using AWS technologies like Glue, Athena, Redshift, and Kinesis.
• Create best practice – establish MLOps processes, model governance, and retraining frameworks from the ground up.
• Collaborate widely* – work with technology, product, and operations teams to uncover high-impact ML use cases and deliver measurable results.

What You Bring

• Hands-on expertise with the AWS ML ecosystem (SageMaker, Glue, Athena, Redshift, Lambda, S3).
• Strong foundations in data science and machine learning, including feature engineering, model evaluation, and optimisation.
• Confident programming skills in Python (pandas, scikit-learn, PyTorch/TensorFlow) and SQL.
• Experience building and deploying ML models in production, with a solid understanding of MLOps.
• A builder’s mindset — comfortable operating with autonomy and ownership in a greenfield environment.

Bonus Points For

• Experience working with financial, registry, or market data.
• Knowledge of AWS Bedrock, Generative AI, or agentic AI frameworks (LangGraph, CrewAI, RAG, MCP).
• Experience using Infrastructure as Code (Terraform or CloudFormation).

Why It’s a Big Deal As the first Machine Learning hire, this person will define how the business approaches AI — from architecture and pipelines to strategy and culture. They’ll have a direct line to leadership, the scope to experiment, and the chance to make visible, high-impact contributions from day one. This is a role for someone who thrives in a fast-moving environment, enjoys solving complex data challenges, and wants to build, not just maintain . If you’re excited by the idea of being the architect of something lasting — and turning financial data into intelligent systems that drive the future of the business — this is the opportunity.