Staff Engineer - ML/AI

Nuage Technology Group; City of Melbourne; Hybrid; AUD 180,000 - 230,000; Full time

Job summary

Nuage Technology Group seeks a Staff Engineer to lead ML/AI capabilities in Melbourne, Australia, with a hands-on, senior IC focus and no people management. You’ll collaborate across engineering to set technical direction and deliver production-grade ML solutions.

The role is permanent in Melbourne with a hybrid work model, balancing close tech work with strategic influence on the ML/AI roadmap and product delivery.

Qualifications

• Hands-on Staff Engineer role with senior IC responsibilities.
• Technical leadership without people management.
• Focus on ML/AI capabilities across products.
• Environment is Databricks and AWS; strong fundamentals matter.

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 shaping the technical roadmap across ML and AI.
• Providing technical leadership and influencing senior engineers.

Skills

Production ML

MLOps

GenAI

LLM workflows

AI agents

Software engineering

Model monitoring

Observability

Lifecycle management

Databricks

AWS

SageMaker

Snowflake

Azure

Technical leadership

Tools

Databricks

AWS

SageMaker

Snowflake

Azure

Job description

Permanent | Melbourne | Hybrid

Staff Engineer - ML/AI

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.