Introduction
MLOps salaries have jumped 18% year-over-year in Australia, making it one of the fastest-growing compensation categories in tech. What's driving the move?
Supply vs Demand
MLOps is a relatively new discipline. Five years ago, it barely existed as a standalone function. Most experienced practitioners came from DevOps or SRE backgrounds and taught themselves ML tooling, Kubernetes, and model serving frameworks. These people are scarce. Every company building ML at scale suddenly needs MLOps expertise, and the supply of qualified people is nowhere near the demand.
The Enterprise Effect
Banks, insurers, and large corporates are all building ML platforms now. They need MLOps engineers to run them. This isn't a startup problem anymore — it's an enterprise problem. And enterprises pay. A mid-market bank wanting to build an internal ML platform will pay top dollar for someone who can architect Kubeflow or SageMaker across multiple business units.
Current Market Rates
Mid-level (3-5 years): AUD 130k-160k total package including superannuation. Senior (5-10 years): AUD 160k-210k. Lead or Principal (10+ years or team leadership): AUD 210k-270k. These are 2026 Sydney/Melbourne rates. Regional and remote roles are slightly lower. The range reflects company stage and AI maturity — early-stage startups pay the low end; established tech companies and enterprises pay the high end.
What's Next
Expect continued growth as generative AI deployments require robust ML infrastructure. Every LLM inference platform, every RAG system, every fine-tuning pipeline needs MLOps. This is structural demand, not a bubble. MLOps is becoming the plumbing of AI, and you need good plumbing.
Want to Discuss This Topic?
If you're hiring MLOps talent, exploring the role, or benchmarking compensation, Sonitec can help you understand the market and find the right people.
Contact Us →