12-month contract + potential 12-month extension
Hybrid working arrangements
Must be able to obtain NV1 security clearance
We're seeking an experienced Machine Learning Engineer to build and support the cloud infrastructure and engineering platforms behind AI, machine learning and data science products.
This role has a strongAWS cloud engineering and DevOps focus.
You'll work with multidisciplinary teams to move solutions from proof of concept through to production, supporting generative AI, retrieval-augmented generation (RAG), automation and analytical applications.
Machine Learning Engineer – AWS / DevOps / AI Platforms
APS6 equivalent | Federal Government
12-month contract + potential 12-month extension
Hybrid working arrangements
Australian citizenship required
Must be able to obtain NV1 security clearance
We're seeking an experienced Machine Learning Engineer to build and support the cloud infrastructure and engineering platforms behind AI, machine learning and data science products.
This role has a strongAWS cloud engineering and DevOps focus.
You'll work with multidisciplinary teams to move solutions from proof of concept through to production, supporting generative AI, retrieval-augmented generation (RAG), automation and analytical applications.
What you'll do
Design, build and maintain AWS infrastructure across development, testing and production environments.
Automate infrastructure provisioning using Terraform, AWS CDK or CloudFormation.
Develop CI/CD pipelines covering build, testing, security scanning and deployment.
Deploy and support containerised applications using Docker, Kubernetes and Amazon EKS.
Manage cloud networking, IAM, compute, storage, application configuration and secrets.




Implement monitoring, logging, dashboards and alerting to improve platform reliability.
Troubleshoot infrastructure, deployment and operational issues, including root cause analysis.
Support security hardening, vulnerability remediation and cloud governance requirements.
Contribute to MLOps and LLMOps capabilities for model deployment, evaluation, monitoring and lifecycle management.
Develop operational runbooks, technical documentation and reusable deployment patterns.
What you'll bring
Demonstrated experience designing, deploying and supportingAWS cloud solutions.
Solid experience developing and maintainingCI/CD pipelines.
Hands-onInfrastructure as Codeexperience using Terraform, AWS CDK, CloudFormation or equivalent.
Experience withDocker and Kubernetes, preferably Amazon EKS.
Experience implementing monitoring, logging and observability for cloud applications and platforms.
Strong troubleshooting skills across complex infrastructure, deployment and operational environments.
The ability to collaborate with data scientists, AI engineers, software engineers and business stakeholders.
Highly regarded
Experience supporting AI, machine learning or data science platforms.
Knowledge ofMLOps, LLMOps, model deployment and monitoring.
Familiarity withAmazon Bedrock, generative AI or RAG solutions.
Experience with cloud security controls, IAM, secrets management and compliance automation.
Eligibility and working arrangements
Applicants must beAustralian citizensand able to obtainNegative Vetting Level 1 (NV1) security clearance.
Evidence of citizenship will be required during pre-engagement checks.
Hybrid working arrangements are available.
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📌 Machine Learning Engineer - Aws / Devops /... (Sydney)
🏢 Talent International
📍 Sydney