Staff Engineer - ML/AI

Nuage; City of Melbourne; Hybrid; AUD 140,000 - 200,000; Full time

Job summary

Nuage in Melbourne is seeking a hands-on Staff Engineer to provide technical leadership across ML, MLOps and Generative AI. This permanent, hybrid role offers real ownership of design and delivery within a growing AI capability.

You’ll build and evolve MLOps, design production GenAI applications, define patterns, and influence senior engineers. The environment centers on Databricks and AWS, with broader cloud experience welcomed to drive robust AI solutions.

Qualifications

• Hands-on software engineering with ML/AI focus.
• Production ML and MLOps experience.
• GenAI, LLM workflows and AI agents.
• Strong software engineering fundamentals.
• Model monitoring, observability and lifecycle management.
• Experience with Databricks and cloud platforms.
• Tech leadership while remaining hands-on.

Responsibilities

• 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.

Skills

Production ML

MLOps

GenAI

LLM workflows

AI agents

Software Eng

Tech leadership

Tools

Databricks

AWS

SageMaker

Snowflake

Azure

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.