Machine Learning Engineer
Own the model lifecycle — training, deployment, monitoring and drift — for a client-facing recommendation platform.
$145,000 – $175,000 / year
About the role
A growing data team needs an ML engineer who treats models as software: versioned, tested, observable and cheap to retrain. You will own the path from notebook to production and the monitoring that says whether the model is still earning its keep.
Responsibilities
Productionise training pipelines; deploy and monitor models on AWS; build feature stores and drift alerts; pair with analysts to turn ad-hoc models into maintained services.
Requirements
Strong Python and SQL; experience shipping and operating ML models in production; comfort with AWS SageMaker or equivalent; MLOps tooling experience valued.
Benefits
Hybrid Sydney CBD, conference budget, ESOP.