Full TimeENNorth America
Property intelligence is reshaping how the world understands the built environment, and Nearmap is driving that. We put powerful aerial imagery, AI-driven analytics, and geospatial tools into the hands of the people who plan, build, insure, and govern the places we all live and work. Our technology turns property uncertainty into decisive action, and our culture brings out the best in the people who build it.
About the Role
We're looking for a Machine Learning Engineer to join our Insurance AI team. You'll be the engineering backbone for our Data Scientists, building and maintaining the ML infrastructure that turns models into reliable, scalable products.
This isn't a greenfield build-everything-from-scratch role. Our Sydney-based AI & Computer Vision team has built robust ML tooling and pipelines. Your job is to extend, adapt, and maintain that infrastructure for US-specific use cases. If you're someone who gets satisfaction from making existing systems work better rather than reinventing the wheel, keep reading.
You'll work closely with Data Scientists in the US and ML Engineers in Australia, acting as the technical bridge that keeps both teams moving fast.
What You'll Do
You'll own the ML engineering function for the US Insurance AI team. That means building data and model pipelines, integrating with internal and external APIs, and making sure our Data Scientists have the tools they need to ship models to production. You'll collaborate daily with our Sydney AICV team to leverage shared infrastructure and contribute improvements back.
Day to day, you'll write Python, wrangle data pipelines, debug production issues, and translate Data Scientist requirements into working systems. You'll use AWS, work with cloud-native technologies, and operate within an established MLOps framework.
Key Responsibilities
You'll need:
It would be great if you also have:
Who You Are
You're mid-career and self-sufficient. You don't need someone looking over your shoulder, but you also know when to ask questions. You'd rather build on a solid foundation than start from scratch just to put your stamp on something. You communicate clearly, collaborate well with remote teams, and care about shipping things that actually work.
To help us get to know the real you: In your application, tell us about a specific ML pipeline you've built or maintained and one thing you learned from it. Skip the AI-generated cover letters. We want to hear your voice.
Why you'll love working at Nearmap:
We move fast and work smart; often wearing multiple hats. We adapted to remote working with ease and are continually looking at ways to improve. We’re proud of our inclusive, supportive culture, and maintain a safe environment where everyone feels a sense of belonging and can be themselves.
In addition to your annual leave, Nearmap offers:
Learn More About The Work We Do
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