Machine Learning Engineer - AWS / DevOps /...

Talent International; Parramatta; Híbrido; AUD 110.000 - 140.000; Jornada completa

Descripción de la vacante

Talent is seeking an experienced Machine Learning Engineer focused on AWS, DevOps and AI platform infrastructure in a hybrid NSW role. The position supports cloud-native AI and data science products from PoC to production, emphasizing scalable AWS infrastructure and secure deployment practices.

The role involves building CI/CD pipelines, implementing IaC with Terraform/AWS CDK/CloudFormation, and deploying containerised apps with Docker/Kubernetes (EKS).

Formación

• Experience designing, deploying and supporting AWS cloud solutions.
• Strong experience developing and maintaining CI/CD pipelines.
• Hands-on Infrastructure as Code using Terraform, AWS CDK, CloudFormation or equivalents.
• Experience with Docker and Kubernetes, preferably Amazon EKS.
• Experience implementing monitoring, logging and observability for cloud apps.
• Strong troubleshooting skills across complex infra, deployment 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 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, app 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.

Conocimientos

AWS cloud solutions

CI/CD pipelines

Infrastructure as Code

Docker

Kubernetes

Monitoring & observability

Troubleshooting

Collaboration

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.

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.