Machine Learning Engineer I

Empregos Em Nicolab; Launceston; Vor Ort; AUD 120.000 - 165.000; Vollzeit

Zusammenfassung

Bailey Abbott is seeking a Machine Learning Engineer with a strong software engineering foundation to productionise, scale, and maintain advanced analytics and predictive models. You will bridge data science experimentation with robust software engineering, designing scalable data pipelines and automated ML lifecycles within our Databricks environment using Spark, R, and modern engineering practices.

You’ll collaborate with data architects and engineers to deliver reliable, scalable solutions

Aufgaben

• Production ML Pipelines: Build, test, and optimize production-grade data processing and model training pipelines in Apache Spark and Databricks.
• MLOps & Lifecycle Automation: Standardise model deployment, versioning, monitoring, and automated retraining workflows (CI/CD, MLflow).
• Code Quality & Architecture: Apply software engineering best practices—modular code architecture, automated testing, containerisation, and version control to analytical and statistical codebases.
• R & Statistical Workloads: Optimise and scale R-based modeling workflows to run efficiently over distributed data architectures using Sparklyr/SparkR.
• Collaboration & Integration: Partner with data architects, data engineers,

Jobbeschreibung

Bailey Abbott are a progressive and dynamic IT Consultancy business working across both Public and Private sectors. People are at the core of everything we do. We’re all about nurturing and inspiring people – ours and our clients. We bring a positive attitude and mindset to everything we do. We confidently use our knowledge and skills to solve problems, finding a better and easier way forward.

We deliver transformational outcomes to take businesses further, fearlessly. Confidence and trust is fundamental to delivering superior outcomes and we take ownership and responsibility for our commitments.

Our People

Our staff are creative, collaborative, and passionate. We’re strong advocates for change, challenging the status quo through new thinking, technology, and practices. Always exploring creative ways to simplify complexity.

Role Overview

We are seeking a Machine Learning Engineer with a strong software engineering foundation to productionise, scale, and maintain advanced analytical and predictive models. In this role, you will bridge the gap between data science experimentation and robust software engineering, designing scalable data pipelines and automated ML lifecycles within our Databricks environment using Spark, R, and modern engineering practices.

Key Responsibilities

• Production ML Pipelines: Build, test, and optimize production-grade data processing and model training pipelines in Apache Spark and Databricks.
• MLOps & Lifecycle Automation: Standardise model deployment, versioning, monitoring, and automated retraining workflows (CI/CD, MLflow).
• Code Quality & Architecture: Apply software engineering best practices—modular code architecture, automated testing, containerisation, and version control to analytical and statistical codebases.
• R & Statistical Workloads: Optimise and scale R-based modeling workflows to run efficiently over distributed data architectures using Sparklyr/SparkR.
• Collaboration & Integration: Partner with data architects, data engineers,