Staff Engineer - ML/AI
A hands-on senior individual contributor role providing technical leadership across a major product company's ML, MLOps and Generative AI capability in Melbourne (hybrid). Day to day: building MLOps (feature stores, model lifecycle, monitoring), designing GenAI/LLM pipelines and agentic workflows, and setting engineering patterns, primarily on Databricks and AWS.
- Compensation
- A$190K / yr
- Location
- Melbourne VIC
- Work setup
- Hybrid
- Seniority
- Staff
- Employment
- Full time
- Experience
- Not specified
- Category
- Ml / AI
- Posted
Skills
Must have
- Software engineering background with strong ML/AI experience, or data science/ML background evolved into production engineering
- Production ML and MLOps experience
- GenAI, LLM workflows and AI agents experience
- Strong software engineering fundamentals
- Model monitoring, observability and lifecycle management
- Technical leadership while remaining hands-on in engineering
Nice to have
- Experience with Databricks, AWS, SageMaker, Snowflake, Azure or similar platforms
Full description
Salary: 190000
**Staff Engineer – ML/AIPermanent | 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 - jennifer@nuagetg.io