Lead ML Engineer & Data Scientist — Build Production AI

The Argyle Network; Sydney; On-site; AUD 120,000 - 170,000; Full time

Job summary

The Argyle Network in Sydney, NSW, AU, is seeking a Machine Learning Engineer / Data Scientist to lead the company’s first dedicated ML capability within its Registry business. This on-site, full-time role offers a rare opportunity to shape the technical direction and build a greenfield ML platform.

You will own end-to-end ML projects, develop models for forecasting and anomaly detection, and design scalable data pipelines using AWS tools.

Qualifications

• Experience building and deploying ML models in production with MLOps.
• Proficiency in Python (pandas, scikit-learn, PyTorch/TensorFlow) and SQL.
• Ability to own end-to-end ML projects in a greenfield environment.

Responsibilities

• Lead the ML journey – end-to-end projects from concept to production deployment and monitoring.
• Build models for anomaly detection, forecasting, and data quality improvement.
• Design scalable data pipelines using AWS Glue, Athena, Redshift, and Kinesis.
• Establish MLOps processes, model governance, and retraining frameworks from the ground up.
• Collaborate with technology, product, and operations teams to deliver measurable ML outcomes.

Skills

AWS ML ecosystem

Data science & ML fundamentals

Python programming

SQL

MLOps

Autonomy/ownership

Tools

SageMaker

Glue

Athena

Redshift

Lambda

S3

Job description

The Argyle Network in Sydney, NSW, AU, is seeking a Machine Learning Engineer / Data Scientist to lead the company’s first dedicated ML capability within its Registry business. This on-site, full-time role offers a rare opportunity to shape the technical direction and build a greenfield ML platform.

You will own end-to-end ML projects, develop models for forecasting and anomaly detection, and design scalable data pipelines using AWS tools.