Senior ML Ops Engineer

Balance Recruitment; Sydney; Hybrid; AUD 140,000 - 190,000; Full time

Job summary

Balance Recruitment is seeking a Senior Machine Learning Ops Engineer for a government-connected agency. You will lead ML Ops strategy, collaborate with data scientists and engineers, and implement scalable AI/ML solutions affecting millions of Australians.

The role focuses on developing CI/CD pipelines, ensuring governance, and delivering robust ML deployments in a large, complex environment. Based in Australia with initial on-site work and subsequent hybrid flexibility.

Qualifications

• Advanced degree in AI/ML related field.
• 3+ years hands-on AI/ML engineering in large environments.
• Experience with ML Ops and deployment automation.

Responsibilities

• Plan and drive data engineering solution development balancing requirements.
• Monitor data standards, architectures, security, and compliance.
• Develop, evaluate, monitor, and deploy ML systems effectively and ethically.
• Lead release planning and risk analysis for deployments.
• Build automated CI/CD pipelines to test and retrain ML models.

Skills

Stakeholder comms

CI/CD leadership

Data engineering

Education

Advanced degree in AI/ML

Tools

Git

SQL

Spark/PySpark

Python

MLflow

Kubeflow

Kubernetes

Linux

Hadoop

Hive

Kafka

OpenShift

Job description

Our client, a leading government agency, is seeking an experienced Senior Machine Learning Ops Engineer to join their dynamic team. This role offers the opportunity to contribute to large-scale AI and ML initiatives that support millions of Australians through cutting-edge government services.

In this senior position, you will lead the development and implementation of ML Ops strategies, collaborating closely with data scientists, engineers, and business stakeholders to ensure alignment with industry standards and organisational goals.

Our client, a leading government agency, is seeking an experienced Senior Machine Learning Ops Engineer to join their dynamic team. This role offers the opportunity to contribute to large-scale AI and ML initiatives that support millions of Australians through cutting-edge government services.

In this senior position, you will lead the development and implementation of ML Ops strategies, collaborating closely with data scientists, engineers, and business stakeholders to ensure alignment with industry standards and organisational goals.

Key Responsibilities

• Plan and drive development of data engineering solutions balancing functional and non-functional requirements.
• Monitor application of data standards, architectures, security, and compliance protocols.
• Develop, evaluate, monitor, and deploy complex machine learning systems effectively and ethically.
• Implement algorithms designed by data scientists while advising on technique effectiveness.
• Lead the assessment, planning, and design of release packages with thorough risk analysis.
• Coordinate release scheduling and communications with technology and business teams.
• Conduct post-release reviews to ensure successful deployments and rollback capabilities.
• Identify and manage adoption of release and deployment automation tools and best practices.
• Build automated CI/CD pipelines to test, deploy, monitor, and retrain ML models continuously.
• Implement ethical AI practices and evaluate privacy risk factors in deployed solutions.
• Communicate complex solution designs to product managers and business stakeholders.
• Stay current with evolving ML model architectures and MLOps best practices.

Technical Skills & Experience

• Advanced degree in computer science, statistics, mathematics, or related fields with a focus on AI/ML.
• Minimum 3 years hands‑on experience in AI/ML engineering, ideally within large, complex environments.
• Expertise with tools and technologies including Git, SQL, Spark/PySpark, Python, MLflow, Kubeflow, Kubernetes (Red Hat OpenShift preferred), Linux, and data storage ecosystems (Hadoop, Hive, Kafka).
• Strong background in containerization, relational databases, and data lakes.
• Demonstrated ability in planning and executing data engineering and machine learning projects aligning with industry standards.
• Experience leading risk assessments and managing deployment releases.

Work Environment and Location

The role is based across capital cities in QLD, VIC, or NSW with an initial onsite requirement for six weeks followed by hybrid working flexibility. Candidates must reside within reasonable travel distance to the work location to ensure onsite availability where necessary.

This is an exceptional opportunity to join our client’s forward‑thinking government agency dedicated to delivering world‑class services through innovative technology solutions.

Balance Recruitment is committed to equal opportunity employment. We celebrate diversity and encourage people from all sections of our community to apply for.