Machine Learning Engineer

Nearmap; Melbourne; Hybrid; AUD 80,000 - 100,000; Full time

Benefits offered by this job

Quarterly wellbeing day off

Access to LinkedIn Learning

Wellbeing and technology allowance

Annual flu vaccinations

Hybrid flexibility

In-office lunch every Tuesday and Thursday

Showers available for cyclists

Job summary

A global tech pioneer in location intelligence is seeking a Software Engineer to build and operate machine learning infrastructure on Kubernetes. The role involves creating tools for the ML lifecycle and implementing best practices for automation and reliability. Ideal candidates have a Bachelor’s degree in Computer Science, strong Python skills, and experience with Docker and Kubernetes. This position offers hybrid work flexibility and various employee benefits.

Qualifications

• 2+ years of experience in software engineering, writing production-grade code.
• Hands-on experience with containerization (Docker) and orchestration (Kubernetes).
• Strong proficiency in Python within a Linux/Unix environment.

Responsibilities

• Design, build, and operate ML infrastructure on Kubernetes.
• Create tooling for the end-to-end ML/LLM lifecycle.
• Implement MLOps principles to improve automation and reliability.

Skills

Python

Kubernetes

Docker

CI/CD

Linux/Unix

Education

Bachelor’s degree in Computer Science or related field

Tools

Terraform

Prometheus

Grafana

Job description

Overview

Nearmap is the Australian-founded, global tech pioneer innovating the location intelligence game. Customers rely on Nearmap for consistent, reliable, high-resolution imagery, insights, and answers to create meaningful change in the world and propel industries forward. Harnessing its own patented camera systems, imagery capture, AI, geospatial tools, and advanced SaaS platforms, Nearmap stands as the definitive source of truth that shapes the livable world.

Job Description

The Machine Learning (ML) Systems Engineer is a key architect of the platform that empowers our teams to build, deploy, and operate AI models at scale. You will design and build the core infrastructure, pipelines, and tools supporting everything from traditional ML to Large Language Models (LLMs). This is a high-impact software engineering role for those passionate about building robust, scalable systems that improve developer velocity and enable the effective application of AI across the organization.

Responsibilities

• Build the Core Platform: Design, build, and operate our ML infrastructure on Kubernetes for model training and inference.
• Develop Force-Multiplier Tools: Create tooling to streamline the end-to-end ML/LLM lifecycle (e.g., experiment tracking, RAG systems, model observability).
• Drive Best Practices: Design and implement MLOps and AIOps principles to improve automation, reliability, and security.
• Collaborate and Enable: Work closely with Data Scientists and ML Engineers as internal customers to understand their needs and accelerate their work.

Qualifications

Key Requirements

• Bachelor’s degree in Computer Science, Engineering, or a related technical field, or equivalent practical experience.
• 2+ years of experience in software engineering, writing production-grade code.
• Strong proficiency in Python within a Linux/Unix environment.
• Hands-on experience with containerization (Docker) and orchestration (Kubernetes).
• Solid grasp of modern software development practices (Git, CI/CD, automated testing).
• Highly Desirable
  • Experience building or managing infrastructure on a major cloud platform (AWS, GCP, Azure).
  • Familiarity with Infrastructure as Code (IaC) tools like Terraform or Pulumi.
  • Practical experience with the MLOps/LLMOps lifecycle and its ecosystem (e.g., vector DBs, serving frameworks).
  • Experience with observability stacks (Prometheus, Grafana) or managing large-scale GPU workloads.

Benefits

• Quarterly wellbeing day off – four additional days off annually for your \'YOU\' Days
• Access to LinkedIn Learning
• Wellbeing and technology allowance
• Annual flu vaccinations
• Hybrid flexibility for this role
• Nearmap subscription
• Stocked kitchen with snacks
• In-office lunch every Tuesday and Thursday at our Sydney CBD office
• Showers available for cyclists or lunchtime gym-goers

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. If you can see yourself working at Nearmap and feel you have the right level of experience, we invite you to get in touch.

Read the product documentation for Nearmap AI: https://docs.nearmap.com/display/ND/NEARMAP+AI

For a deep dive into Nearmap AI, listen to AI Systems Senior Director Mike Bewley on the Mapscaping podcast: https://mapscaping.com/blogs/the-mapscaping-podcast/collecting-and-processing-aerial-imagery-at-scale

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