Machine Learning Engineer

Mane Consulting; Sydney; On-site; AUD 140,000 - 180,000; Full time

Job summary

On in Sydney seeks a Senior Machine Learning Engineer to build production-grade ML pipelines powering our marketing platforms. You’ll collaborate with data scientists, engineers, and product teams to design, test, and deploy scalable ML solutions that drive customer engagement and business growth.

You’ll own end-to-end model lifecycles, implement MLOps, monitor performance, and ensure reliability across cloud environments such as GCP or AWS.

Qualifications

• 6+ years delivering complex ML systems with end-to-end pipelines
• Hands-on experience with tools such as Kubeflow, MLflow or Airflow
• Strong Python engineering skills and ML knowledge
• Experience deploying ML workloads on GCP or AWS

Responsibilities

• Transform prototypes into robust ML services across marketing platforms
• Design, automate, and maintain scalable ML pipelines with MLOps frameworks
• Collaborate with cross-functional teams to translate business needs into technical ML solutions
• Help elevate engineering quality, documentation, and operational discipline across ML lifecycle

Skills

Python

MLOps

Kubeflow

MLflow

Airflow

Deep learning

Embeddings

Clustering

Predictive modelling

Kubernetes

Docker

Vertex AI

GCP

AWS

Tools

Kubeflow

MLflow

Airflow

Docker

Kubernetes

Vertex AI

GCP

AWS

Job description

As a Senior Machine Learning Engineer, you’ll play a central role in building and automating production?level machine learning pipelines that power our marketing programs at On. You’ll work closely with business, marketing, and data science teams to design, test, and deploy scalable, reliable solutions that sit at the core of our marketing technology stack. You’ll be joining a growing, diverse team of data engineers, data scientists, and product managers who are passionate about transforming how we use AI and ML across the business-developing innovative systems that enhance customer experiences, optimise internal processes, and drive growth across areas ranging from e?commerce to supply chain optimisation.
In the dynamic landscape of On Data, Machine Learning and AI play a crucial role in accelerating our business growth and operations. We are enhancing our technology landscape to fuel the growth of On, helping to ignite the human spirit through movement.

What you’ll do;

• Partner with data scientists to transform prototypes into robust, high?performing machine learning services integrated across our marketing platforms-from email and advertising to app?based engagement.
• Design, automate, and maintain data and model pipelines that are resilient, observable, and built for scale. Develop MLOps frameworks that monitor performance, trigger alerts, and ensure models remain accurate and available.
• Collaborate with cross?functional teams to understand business needs and translate them into technical solutions. Contribute to the evolution of our MLOps standards, tooling, and best practices.
• Help elevate engineering quality, documentation, and operational discipline across the ML lifecycle.

What you bring;

• 6+ years delivering complex ML systems, with hands?on experience designing end?to?end pipelines using tools such as Kubeflow, MLflow, or Airflow. Strong Python engineering skills.
• Solid grounding in deep learning, embeddings, clustering, and predictive modelling, with a track record of applying these techniques in production.
• Comfort working with modern AI/ML platforms and components-Vertex AI, Docker, Kubernetes, or similar.
• Experience deploying and operating ML workloads on cloud environments such as GCP or AWS.