Overview

6 months initial contract with possible extension

Adelaide Based Position

Duties and Responsibilities

- Design, implement, and maintain ML pipelines for model training, deployment, and monitoring.
- Develop automation and CI/CD workflows for ML models using tools such as
- Ensure compliance with Australian Government security frameworks (ISM, PSPF) and agency policies.
- Optimise ML infrastructure for performance, scalability, and cost-effectiveness.
- Collaborate with data professionals to transition models from development to production.
- Implement monitoring and alerting for model performance and data drift.
- Provide technical advice and mentorship to team members and stakeholders.
- Stay current with emerging ML Ops technologies and best practices.

Qualifications





- Demonstrated experience in ML Ops or related roles within complex environments.
- Robust knowledge of ML lifecycle management and deployment strategies.
- Proficiency in cloud platforms (AWS, Azure, GCP) and containerisation (Docker, Kubernetes).
- Experience with ML Ops tools (Kubeflow, MLflow, Airflow) and CI/CD pipelines.
- Solid understanding of data engineering, version control (Git), and automation frameworks.
- Excellent problem-solving skills and ability to work under pressure.

Apply now or reach to Ivan Aureus at for a confidential chat!

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📌 Machine Learning Engineers (South Australia)
🏢 Talent
📍 South Australia