Machine Learning Engineer - AWS / DevOps / AI Platforms

Talent; Parramatta; Híbrido; AUD 90.000 - 120.000; Jornada completa

Descripción de la vacante

Talent is seeking an experienced Machine Learning Engineer to build and support cloud infrastructure and engineering platforms behind AI, ML and data science products. The role emphasizes AWS cloud engineering and DevOps, moving solutions from proof of concept to production with generative AI, RAG, automation and analytics.

You will design and maintain AWS infrastructure, automate provisioning with Terraform or CDK, and develop CI/CD pipelines.

Formación

• Experience designing and deploying AWS cloud solutions.
• Strong CI/CD pipeline development experience.
• Hands-on IaC with Terraform, AWS CDK, CloudFormation or equivalent.
• Experience with Docker and Kubernetes (preferably Amazon EKS).
• Experience implementing monitoring, logging and observability for cloud apps.
• Strong troubleshooting across complex infra, deployments and operations.
• Ability to collaborate with data scientists, AI engineers, software engineers and stakeholders.

Responsabilidades

• Design, build and maintain AWS infrastructure across development, testing and production.
• Automate infrastructure provisioning using IaC tools like Terraform, AWS CDK or CloudFormation.
• Develop CI/CD pipelines for build, test, security scanning and deployment.
• Deploy and support containerised apps using Docker, Kubernetes and EKS.
• Manage cloud networking, IAM, compute, storage, config and secrets.
• Implement monitoring, logging, dashboards and alerts to improve reliability.
• Troubleshoot infra, deployment and operational issues.
• Support security hardening and governance requirements.
• Contribute to MLOps/LLMOps for model deployment and monitoring.
• Develop runbooks, docs and reusable deployment patterns.

Conocimientos

AWS cloud

CI/CD

Infrastructure as Code

Docker

Kubernetes

Monitoring/Observability

Troubleshooting

Collaboration with data scientists/AI/

Herramientas

Terraform

AWS CDK

CloudFormation

Docker

Kubernetes

Amazon EKS

Descripción del empleo

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 strong AWS 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

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 strong AWS 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 supporting AWS cloud solutions.
• Strong experience developing and maintaining CI/CD pipelines.
• Hands-on Infrastructure as Code experience using Terraform, AWS CDK, CloudFormation or equivalent.
• Experience with Docker 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 of MLOps, LLMOps, model deployment and monitoring.
• Familiarity with Amazon Bedrock, generative AI or RAG solutions.
• Experience with cloud security controls, IAM, secrets management and compliance automation.

Eligibility and working arrangements

Applicants must be Australian citizens and able to obtain Negative Vetting Level 1 (NV1) security clearance. Evidence of citizenship will be required during pre-engagement checks.

Hybrid working arrangements are available.

Desired Skills and Experience

• Amazon Web Services (AWS)
• CI/CD
• Terraform
• AWS CDK / CloudFormation
• Docker
• Kubernetes / Amazon EKS
• Monitoring & Observability
• Cloud Security & IAM
• MLOps / LLMOps
• Amazon Bedrock
• Generative AI / RAG