DevOps Engineer - Machine Learning Platforms

Talent; Melbourne; On-site; AUD 110,000 - 150,000; Full time

Job summary

Our client is a Federal Government agency in Melbourne seeking an APS6 Machine Learning DevOps Engineer to design, deploy and maintain secure, scalable cloud infrastructure for AI and data science workloads. The role focuses on AWS, DevOps, automation and MLOps from proof of concept to production.

You will work with Data Scientists and Software Engineers, implement Terraform IaC, CI/CD pipelines, Docker/Kubernetes, and secure deployment practices, with NV1 security clearance required.

Qualifications

• Strong AWS experience designing, deploying and securing cloud infrastructure.
• Hands-on IaC with Terraform and container orchestration (Docker/Kubernetes).
• Experience building CI/CD pipelines and automated deployments.
• Familiarity with AI/ML platforms and MLOps concepts is a plus.
• Understanding of cloud security, IAM, networking and governance.
• Ability to collaborate with Data Scientists and Software Engineers.

Responsibilities

• Design, build and maintain AWS cloud infrastructure for AI workloads.
• Develop and manage Terraform infrastructure as code.
• Create and maintain CI/CD pipelines for builds, tests and deployments.
• Deploy and manage containerised apps with Docker, Kubernetes, EKS.
• Implement monitoring, logging and observability for reliability.
• Troubleshoot complex cloud and deployment issues in production.
• Support deployment of AI/ML models, APIs and data products.

Skills

AWS cloud engineering

Terraform

CI/CD pipelines

Docker

Kubernetes

EKS

Bedrock / generative AI

Security & IAM

Tools

Terraform

Docker

Kubernetes

EKS

Bedrock

Job description

Our client is a Federal Government agency seeking an experienced APS6 Machine Learning DevOps Engineer to support the development and delivery of cloud-based AI, machine learning and data science solutions. This is a hands-on engineering role with a strong focus on AWS infrastructure, DevOps, automation and MLOps, supporting innovative AI products from proof of concept through to production.

• Federal Government opportunity, requires NV1 Security Clearance
• Strong AWS, DevOps and AI platform focus

The role

Working within a multidisciplinary AI and Data Science team, the Machine Learning Engineer will be responsible for designing, deploying and maintaining secure, scalable cloud infrastructure and engineering platforms. The role combines hands-on AWS cloud engineering, Infrastructure as Code, CI/CD and containerisation with the opportunity to support emerging AI technologies, including generative AI, MLOps, LLMOps and retrieval-augmented generation (RAG) solutions.

Key responsibilities

• Design, build and maintain AWS cloud infrastructure supporting AI, machine learning and data science workloads.
• Develop and manage Infrastructure as Code using Terraform
• Build and maintain CI/CD pipelines to automate application builds, testing, security scanning and deployments.
• Deploy and support containerised applications using Docker, Kubernetes and Amazon EKS.
• Implement monitoring, logging, alerting and observability solutions to improve platform reliability and performance.
• Troubleshoot complex cloud infrastructure, application deployment and operational issues.
• Support the deployment and operational management of AI/ML models, APIs, generative AI applications and data products.
• Implement cloud security controls, IAM, secrets management and secure deployment practices.
• Collaborate with Data Scientists, AI Engineers and Software Engineers to transition solutions from proof of concept through to production.

About you

• Strong commercial AWS experience designing, deploying and supporting cloud infrastructure
• AWS technical skills including Bedrock, S3, Lambda, SQS, SNS
• Demonstrated experience building and maintaining CI/CD pipelines and automated deployment processes
• Hands-on experience with Infrastructure as Code, particularly Terraform
• Strong containerisation and orchestration skills using Docker, Kubernetes, EKS
• Exposure to AI/ML platforms, MLOps, LLMOps, Amazon Bedrock or generative AI/RAG solutions will be highly regarded
• Experience implementing cloud monitoring, logging and observability solutions
• Proven troubleshooting skills across cloud infrastructure, deployments and application environments
• Understanding of cloud security, IAM, networking and platform governance
• Strong communication skills and the ability to work collaboratively within multidisciplinary technical teams.

Please note that role will require an NV1 Security Clearance, so only candidates with Australian citizenship and an NV1 clearance or at least a Baseline clearance can be considered for this role.