Production ML Engineer: Spark, Databricks & MLOps

Empregos Em Nicolab; Launceston; On-site; AUD 120,000 - 165,000; Full time

Job summary

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

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,

Job description

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