Full Stack Machine Learning Engineer

P&C Partners Pty Ltd; City of Brisbane; On-site; AUD 90,000 - 120,000; Full time

Job summary

A leading SaaS provider in Brisbane is seeking a Full Stack Machine Learning Engineer to join their R&D team. You will design and deploy ML models for predictive maintenance using one of the richest industrial datasets. The ideal candidate has over 3 years of experience in machine learning, strong Python skills, and a track record in deploying models. Competitive salary, flexible hybrid working arrangements, and professional development opportunities are offered.

Benefits

Competitive salary

Performance bonus

Flexible hybrid working arrangements

Professional development opportunities

Wellbeing initiatives

Qualifications

• 3+ years of experience in machine learning engineering, including at least 1 year in industrial applications.
• Strong proficiency in Python for ML development.
• Proven track record of deploying ML models into production.

Responsibilities

• Design, build, and deploy production-grade ML models.
• Collaborate with domain experts and product teams.
• Work hands-on with one of the world’s richest industrial datasets.

Skills

Machine learning engineering

Python

ML frameworks (TensorFlow, PyTorch)

Deploying ML models

MLOps tools

Data pipelines and ETL

Cloud deployment (AWS, Azure, GCP)

Interpretable ML techniques

Tools

Docker

Kubernetes

Job description

Overview

Cloud-based platform delivering AI-powered predictive maintenance and asset reliability for large-scale industrial operations.

The Company

This fast-growing, private-equity-backed SaaS business is redefining how asset-intensive industries harness data and AI to drive reliability and performance. Their enterprise platform is trusted by global leaders, delivering smarter, faster, and more accurate insights for large-scale operations. With a modern technology stack, a collaborative engineering culture, and an ambitious growth trajectory, they offer the chance to help shape the future of industrial intelligence.

The Role

As a Full Stack Machine Learning Engineer, you’ll join a high-performing R&D team working on mission-critical AI solutions for predictive maintenance and operational optimisation. Reporting to the Manager of AI & Data Science, you’ll design, build, and deploy production-grade ML models that power real-time decision support and automation across complex environments. You’ll work hands-on with one of the world’s richest industrial datasets, collaborating with domain experts and product teams to deliver solutions that make a measurable impact in the field.

About You

You’re a technically strong and ambitious ML engineer who thrives in collaborative, fast-paced environments. You enjoy solving complex problems, building scalable solutions, and working across modern frameworks and cloud platforms. With a solid grounding in end-to-end ML development and a passion for deploying models that deliver real-world results, you’re eager to keep learning and contribute ideas that push the boundaries of industrial AI.

Skills & Experience

• 3+ years of experience in machine learning engineering, including at least 1 year in industrial applications (IoT, predictive analytics, fleet telemetry, or similar)
• Strong proficiency in Python for ML development
• Experience with ML frameworks (TensorFlow, PyTorch) and libraries (scikit-learn, Hugging Face)
• Proven track record of deploying ML models into production (time-series forecasting, anomaly detection, classification)
• Hands-on experience with MLOps tools (MLflow, Kubeflow, SageMaker, or similar) for model versioning, monitoring, and retraining
• Familiarity with agentic AI concepts (multi-agent systems, human-in-the-loop implementations)
• Understanding of data pipelines and ETL for multimodal datasets (sensor, image, text, telemetry)
• Cloud deployment experience (AWS, Azure, or GCP) with containerisation (Docker, Kubernetes)
• Knowledge of interpretable ML techniques (e.g., SHAP, LIME)

Valuable extras

• Experience with predictive maintenance or condition monitoring
• Exposure to computer vision (thermal imaging, defect detection)
• Familiarity with graph neural networks or multimodal AI
• Contributions to open-source ML projects or publications in industrial AI

What’s on Offer

• Competitive salary and performance bonus
• Flexible hybrid working arrangements
• Dedicated professional development opportunities
• Inclusive, collaborative company culture
• Support for work-life balance, including extra leave and wellbeing initiatives

Apply Now

If you’re ready to make an impact in a fast-growing SaaS business and help deliver AI solutions that transform asset reliability and performance, apply today! Click “Apply Now” or reach out to the Brisbane office for a confidential discussion.