Senior ML Engineer — Scalable Pipelines & MLOps

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

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.