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Full timeTechnology

Staff ML/AI Engineer - GenAI & MLOps Leader

NuageMelbourne, Melbourne🇦🇺AustraliaPosted 5 Oct 2026

Why this role stands out

This hybrid role at Nuage offers a fantastic opportunity to lead the design and delivery of cutting-edge GenAI and MLOps solutions, providing significant ownership and impact within a growing AI capability. You'll thrive if you're a hands-on engineer eager to build robust AI systems on Databricks and AWS, influencing technical direction and shaping the future of AI at the company. Apply now to take your career to the next level!

Quick overview

SeniorityMid Senior
Employment typeFull Time
Work modeHybrid
LocationMelbourne, Melbourne, Australia
AWSMLOpsSnowflakeAzureDatabricksGenerative AILLM

Job description

  • Staff-level IC with real technical ownership
  • Production GenAI, agents & MLOps
Staff Engineer - ML/AI
Permanent Melbourne Hybrid

We're working with a major product company looking for a hands-on Staff Engineer to provide technical leadership across its growing ML, MLOps and Generative AI capability.
This is a senior individual contributor role with no people management. You'll work across different engineering teams, helping set technical direction while remaining close to the technology and delivery.
What you'll be working on
  • Building and evolving MLOps capabilities across feature stores, model lifecycle, drift detection, monitoring and observability.
  • Designing production GenAI applications, LLM pipelines, agentic workflows and guardrails.
  • Setting engineering patterns and helping shape the technical roadmap across ML and AI.
  • Providing technical leadership and influencing senior and Principal Engineers.
  • Working on established AI products already delivering measurable improvements to customer and internal workflows.

What we're looking for
You'll ideally come from either a software engineering background with strong ML/AI experience, or a data science/ML background that has evolved into production engineering.
We're particularly interested in experience across:
  • Production ML and MLOps.
  • GenAI, LLM workflows and AI agents.
  • Strong software engineering fundamentals.
  • Model monitoring, observability and lifecycle management.
  • Databricks, AWS, SageMaker, Snowflake, Azure or similar platforms.
  • Technical leadership without moving away from hands-on engineering.

The environment is primarily Databricks and AWS, although exact tool matching isn't essential. Strong engineering and ML/AI fundamentals matter more.
This would suit someone who wants to remain deeply technical while having genuine ownership over how ML and AI solutions are designed and delivered.
Apply now -

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