Machine Learning & MLOps Engineers | Federal Government
Location: Canberra,Melbourne,Brisbane,Hobart,Adelaide,Sydney
About the Role:
We are seeking experienced Machine Learning Engineers and MLOps Engineers to support a major Federal Government client. You will be instrumental in designing, deploying, and scaling sophisticated ML solutions within a secure, high-impact environment.
These roles require a blend of technical excellence and the ability to navigate Australian Government security frameworks.
Australian Citizen's with a current Baseline Security Clearance (or higher) are highly desirable.
Machine Learning Engineer
Focus: Designing and implementing high-performance models.
Key Responsibilities:
* Design and implement ML models and algorithms for complex, large-scale datasets.
* Develop and maintain robust ML pipelines for training, testing, and deployment.
* Optimize production models for performance, scalability, and accuracy.
* Ensure all solutions comply with the ISM, PSPF, and ethical AI principles.
* Monitor model health, detecting and addressing data drift.
Your Toolkit:
* Expertise in Python and frameworks (TensorFlow, PyTorch, Scikit-learn).
* Deep understanding of feature engineering and model optimization.
* Experience with cloud platforms (AWS, Azure, or GCP) and Docker/Kubernetes.
MLOps Engineer
Focus: Automation, CI/CD, and the ML lifecycle.
Key Responsibilities:
* Design and maintain end-to-end ML pipelines and infrastructure.
* Develop automation and CI/CD workflows to transition models from dev to production.
* Implement monitoring and alerting for model performance and data integrity.
* Optimize infrastructure for cost-effectiveness and scalability.
* Provide technical mentorship and ensure adherence to ISM/PSPF security standards.
Your Toolkit:
* Strong experience with MLOps tools (Kubeflow, MLflow, or Airflow).
* Proficiency in containerization and cloud infrastructure
* Background in Data Engineering and version control (Git).