A leading Australian organisation is investing heavily in advanced data, AI and machine learning capabilities to support large-scale, mission-critical operations. An opportunity now exists for an experienced MLOps Engineer to play a key role in taking machine learning models from prototype through to reliable, cost-effective production.

The Role
As an MLOps Engineer, you will be responsible for the full lifecycle of ML/AI solutions in production. You will work closely with Data Scientists, Data Engineers, DevOps and application teams to design, deploy and operate scalable machine learning systems in a cloud environment.

Key responsibilities include:

• Transitioning machine learning models from Databricks notebooks into production using best-practice ML and pipeline patterns
• Designing, building and maintaining end-to-end ML and data pipelines
• Maintaining and optimising Databricks infrastructure (compute, catalogues, users, upgrades)
• Monitoring performance, cost, stability and operational efficiency of ML platforms
• Writing and reviewing technical documentation, designs and code