Senior MLOps Engineer - Production ML Pipelines (Hybrid)

Talent; Sydney; Hybrid; AUD 170,000 - 210,000; Full time

Job summary

Talent is seeking a Senior MLOps Engineer to support a major Federal Government organisation. You will design and operate automated MLOps pipelines, build data workflows and containerised ML environments with Kubernetes and OpenShift AI.

Collaborate with data scientists and engineers to deploy secure, scalable ML solutions. Responsibilities include testing, release management, model monitoring and responsible AI practices.

Qualifications

• Hands-on AI/ML engineering experience delivering production ML solutions.
• Strong programming and data engineering with Python, SQL and Spark/PySpark.
• Experience with MLOps frameworks like MLflow or Kubeflow for tracking, versioning and monitoring.
• Kubernetes, containerisation and Linux experience, ideally Red Hat OpenShift AI.
• CI/CD, Git, infrastructure automation and secure release practices.

Responsibilities

• Design, develop and maintain automated MLOps pipelines for model development, testing, deployment, monitoring and retraining.
• Build batch and real-time data pipelines to support enterprise ML workloads.
• Manage containerised ML environments using Kubernetes and OpenShift AI.
• Collaborate with data scientists and engineers to transition models into production.
• Establish automated testing, release management and secure deployment processes.
• Implement model monitoring, experiment tracking and version control for reliability.

Job description

Talent is seeking a Senior MLOps Engineer to support a major Federal Government organisation. You will design and operate automated MLOps pipelines, build data workflows and containerised ML environments with Kubernetes and OpenShift AI.

Collaborate with data scientists and engineers to deploy secure, scalable ML solutions. Responsibilities include testing, release management, model monitoring and responsible AI practices.