MLOps Engineer / Machine Learning Engineer - Python, Kubernetes, MLflow, PySpark

Infinity Pro; Sydney; On-site; AUD 110,000 - 165,000; Full time

Job summary

Infinity Pro is seeking an experienced MLOps Engineer / Machine Learning Engineer for a senior contract with a Federal Government agency.

You will help turn machine-learning solutions into reliable production services, combining data pipelines, model integration, automated testing, deployment, monitoring and retraining. Working with data scientists, engineers and business stakeholders, you will also contribute to MLOps strategy, engineering standards and secure, maintainable delivery.

Qualifications

• At least three years’ AI/ML engineering experience with deployment and monitoring of ML systems.
• Strong data-engineering capability including Python, APIs, SQL and Spark/PySpark, with batch and streaming pipelines.
• Practical experience with Git, Linux, containerisation, Kubernetes and automated CI/CD, plus MLflow/Kubeflow or equivalent platforms.

Responsibilities

• Build and operate batch and streaming data pipelines for ML workloads.
• Implement models and integrate with data stores and computing environments.
• Develop automated pipelines for testing, deployment and monitoring of ML models.
• Lead testing, release planning and risk assessments for production ML workloads.
• Contribute to MLOps strategy, security and governance in collaboration with stakeholders.

Skills

AI/ML engineering

Data engineering

CI/CD

Git

Linux

Containerisation

Kubernetes

MLflow/Kubeflow

Education

Advanced degree in CS/Statistics/Math

Tools

Python

Spark/PySpark

Kubernetes

MLflow

Kubeflow

Git

Linux

OpenShift

Job description

• Initial contract of up to 12 months, with extension options up to a maximum of 24 months
• Competitive rates - please advise your hourly expectations
• Production machine learning, data engineering and automated model delivery
• Python, Spark/PySpark, Kubernetes and MLflow/Kubeflow or equivalent tooling
• Sydney, Melbourne or Brisbane; initial six weeks onsite unless otherwise negotiated
• Baseline clearance eligibility required, with clearance in place before commencement

• Initial contract of up to 12 months, with extension options up to a maximum of 24 months
• Competitive rates - please advise your hourly expectations
• Production machine learning, data engineering and automated model delivery
• Python, Spark/PySpark, Kubernetes and MLflow/Kubeflow or equivalent tooling
• Sydney, Melbourne or Brisbane; initial six weeks onsite unless otherwise negotiated
• Baseline clearance eligibility required, with clearance in place before commencement

Infinity Pro is seeking an experienced MLOps Engineer / Machine Learning Engineer for a senior contract opportunity within a Federal Government agency.

You will help turn machine-learning solutions into reliable production services, combining data pipelines, model integration, automated testing, deployment, monitoring and retraining. Working with data scientists, engineers and business stakeholders, you will also contribute to MLOps strategy, engineering standards and secure, maintainable delivery.

This opportunity suits a hands-on ML Platform Engineer, or a data/software engineer with substantial production machine-learning experience - not solely model research or proof-of-concept development.

Essential Experience

• At least three years’ AI/ML engineering experience, with a proven record contributing to the development, evaluation, deployment and monitoring of machine-learning systems.
• Strong data-engineering capability, including Python, APIs, SQL and Spark/PySpark, batch and streaming pipelines, and data solutions spanning relational databases, distributed file systems, blob storage and data lakes.
• Practical experience with Git, Linux, containerisation, Kubernetes and automated CI/CD, together with model-lifecycle tooling such as MLflow, Kubeflow or an equivalent platform.
• Ability to lead testing and release/deployment activities: test planning, automation, risk assessment, release readiness, rollback planning and post-release reviews.
• Experience applying data standards, architecture, security and compliance requirements, assessing privacy and ethical-AI risks, and communicating technical designs to engineering and business stakeholders.
• An advanced degree in computer science, statistics, mathematics or a related field, with a focus on data science, machine learning or artificial intelligence.

Highly regarded but not essential

• Current Baseline or higher security clearance
• Red Hat OpenShift experience.
• Well-developed software-engineering practices: designing, coding, verifying, documenting and refactoring programs or scripts, applying agreed standards and contributing to peer reviews.
• Current Baseline Security Clearance

What you will work on

• Build and improve batch and streaming data pipelines supporting ML workloads, including integration with databases, distributed storage and data-lake technologies such as Hadoop, Hive, Impala and Kafka.
• Implement algorithms developed by data scientists and contribute to model evaluation, deployment, monitoring and retraining.
• Develop automated pipelines that test, deploy and monitor models, supporting repeatable releases and effective operational controls.
• Lead testing across delivery stages, improve automation and standards, assess risks and support reliable release decisions.
• Plan release packages, coordinate deployment schedules, maintain rollback capability and conduct post-release reviews.
• Contribute to MLOps strategy and engineering guidance, working across data science, engineering, product and business teams.

Location and working arrangements

The position can be based in Sydney, Melbourne or Brisbane.

You will be expected to work onsite for the first six weeks, unless otherwise negotiated. A hybrid arrangement may then be considered; it is not guaranteed from commencement.

You must live within reasonable travelling distance of the relevant office and be able to attend onsite for business requirements or emergencies.

Security clearance

Candidates must be eligible to obtain and maintain Australian Government Baseline security clearance, which is required before starting work.

Applicants already holding current Baseline, NV1 or NV2 clearance are encouraged to apply. Please state your citizenship and current clearance status with your application.

The opportunity

An initial contract of up to 12 months, with extension options up to a maximum of 24 months, and an estimated commencement of 1 December 2026. The brief allows up to 50 hours per week; the actual working schedule will need to be confirmed.

You will combine hands-on engineering with the opportunity to influence how machine-learning solutions are tested, released and operated in a complex government environment.