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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- Robust 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 0480 806 152 for a confidential chat!

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