Senior MLOps Engineer — Secure, Scalable ML Deployments

Exclaim IT; Sydney; On-site; AUD 130,000 - 180,000; Full time

Job summary

Exclaim IT is seeking an experienced MLOps Engineer to support the development, deployment and ongoing management of machine learning solutions within a government environment. You will establish MLOps strategies, develop automated deployment pipelines and ensure secure, scalable ML systems aligned with business goals.

Key responsibilities include building CI/CD pipelines, data engineering solutions, collaboration with data scientists, and leading release planning with emphasis on testing,

Qualifications

• At least three years of AI/ML engineering experience with deployment focus.
• Experience implementing data solutions with SQL, Spark and data pipelines.
• Strong programming in Python and ML frameworks.
• Familiar with CI/CD, testing, monitoring, and retraining processes.
• Experience with data lakes and distributed data technologies.

Responsibilities

• Develop and maintain automated CI/CD pipelines to test, deploy, monitor and retrain models.
• Plan and deliver data engineering solutions balancing performance, security and governance.
• Collaborate with scientists and engineers to implement ML algorithms and integrate with systems.
• Lead release planning, deployment automation and rollback procedures.
• Ensure ethical AI practices, privacy risk management and policy compliance.
• Communicate designs and progress with product managers and stakeholders.
• Monitor emerging MLOps technologies and drive continuous improvement.

Skills

Python programming

SQL

Spark/PySpark

Git

Linux

Stakeholder communication

Problem solving

Education

Advanced degree in Computer Science, Statistics, Mathematics or related field

Tools

MLflow

Kubeflow

OpenShift

Kubernetes

Hadoop

Hive

Impala

Kafka

Job description

Exclaim IT is seeking an experienced MLOps Engineer to support the development, deployment and ongoing management of machine learning solutions within a government environment. You will establish MLOps strategies, develop automated deployment pipelines and ensure secure, scalable ML systems aligned with business goals.

Key responsibilities include building CI/CD pipelines, data engineering solutions, collaboration with data scientists, and leading release planning with emphasis on testing,