Senior Machine Learning Engineer (Platform / MLOPs)

About Nearmap

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 Senior MLOps Engineer to join our Platform team in Sydney. This is a genuine opportunity to own greenfield platform work at serious scale. Nearmap is one of the top three AWS users in the APAC region. The systems you'll build aren't theoretical — they're processing aerial imagery across Australia, the US, and Canada, and serving AI models to real customers at high concurrency.

You'll sit between traditional DevOps and the new world of AI engineering — which means this role suits someone with a strong back-end and platform engineering foundation who is ready to grow their career into AI, or who is already making that transition. AI experience is a bonus, not a barrier to entry — we can coach that side as a team.

Key Responsibilities

You'll own projects end to end — from architecture and design through to implementation, delivery, and production operations. That kind of trust and autonomy is real here, not a recruitment line.

Day to day that looks like:

• Designing and building scalable ML infrastructure — large-scale batch inference on EKS, real-time model serving via Ray Serve, and GPU-accelerated distributed training on GCP and AWS
• Building the LLM platform that will underpin Nearmap's next generation of generative AI products — including deployment, governance, experimentation, and cost optimisation across CPU/GPU workloads
• Owning developer experience for AICV engineering teams — CI/CD pipelines, Docker tooling, ArgoCD, W&B, and Arize AI
• Driving reliability and observability across production ML systems with real SLAs and SLOs
• Contributing production-quality Python to shared platform libraries and services
• Playing a tech lead role on your primary project, with advisory exposure across others
• Engaging directly with ML tooling vendors including AWS, GCP, Weights & Biases, Confluent, and Arize AI

The teams depending on your platform include Model R&D, Computer Vision, Insurance Data Science, Agentic AI, and AI Map Data.

Required Qualifications

• Production experience building and operating Kubernetes-based platforms (EKS/GKE) at scale
• High-scale, high-concurrency API development and operation in production environments
• Real operational mindset: you've managed systems with SLAs and SLOs and stayed close through incidents
• Strong DevOps fundamentals — CI/CD, infrastructure-as-code, deployment pipelines
• Production-level Python — services and libraries, not just scripts

Highly Valued Qualifications

• Ray Serve or equivalent real-time model serving experience
• LLM or generative AI platform work in production (beyond PoC)
• ML observability tooling — Arize AI, Evidently, Prometheus/Grafana
• Infrastructure-as-code with Terraform
• Experience at terabyte or petabyte scale
• GPU/CPU cost optimisation

A degree in computer science, engineering, mathematics, or a related field is welcome — equivalent practical experience is equally valued.

Location and Working Arrangements

This role is based in our Barangaroo, Sydney office, with an expectation of at least two days per week on-site.

This role is open to Australian citizens and permanent residents, or those with full working rights in Australia.

Benefits

• Quarterly wellbeing day off — Four additional days off annually for your 'YOU' Days
• Wellbeing and technology allowance
• Annual flu vaccinations
• Hybrid flexibility for this role
• Nearmap subscription
• Stocked kitchen with access to all the snacks you need
• In-office lunch every Tuesday and Thursday at our Sydney CBD office
• Showers available for anyone cycling to work or lunchtime gym-goers

About Working at Nearmap

We move fast, we care about craft, and we're proud of what we're building. If you're energised by turning hard problems into real-world impact, we'd love to meet you.

Note: Nearmap does not accept unsolicited resumes from recruitment agencies and search firms. Please do not email or send unsolicited resumes to any Nearmap employee, location or address. Nearmap is not responsible for any fees related to unsolicited resumes.