Job Description
Overview
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6 months initial contract with possible extension
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Adelaide Based Position
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Duties and Responsibilities
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Design, implement, and maintain ML pipelines for model training, deployment, and monitoring.
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Develop automation and CI/CD workflows for ML models using tools such as
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Ensure compliance with Australian Government security frameworks (ISM, PSPF) and agency policies.
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Optimise ML infrastructure for performance, scalability, and cost-effectiveness.
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Collaborate with data professionals to transition models from development to production.
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Implement monitoring and alerting for model performance and data drift.
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Provide technical advice and mentorship to team members and stakeholders.
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Stay current with emerging ML Ops technologies and best practices.
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Qualifications
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Demonstrated experience in ML Ops or related roles within complex environments.
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Solid knowledge of ML lifecycle management and deployment strategies.
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Proficiency in cloud platforms (AWS, Azure, GCP) and containerisation (Docker, Kubernetes).
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Experience with ML Ops tools (Kubeflow, MLflow, Airflow) and CI/CD pipelines.
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Solid understanding of data engineering, version control (Git), and automation frameworks.
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Excellent problem-solving skills and ability to work under pressure.
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Apply now or reach to Ivan Aureus at ************ for a confidential chat!
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📌 Machine Learning Engineers (South Australia)
🏢 Talent
📍 South Australia