Machine Learning Engineer - Deep Learning Specialist (Computer Vision)

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.

We are recruiting a hands-on Machine Learning Engineer with a passion for R&D and strong expertise in applying deep learning techniques to practical computer vision applications. You will work with an incredibly passionate and talented team of Data Scientists and Machine Learning Engineers, and your work will have a real impact on Nearmap products. You will train novel deep learning models that leverage our rich data sets, multiple dates of high-resolution imagery, multi-angle source imagery and 3D textured mesh. You will collaborate closely with other team members to solve various 2D and 3D vision tasks by selecting the model architecture, designing training and evaluation methodologies, generating a suitable dataset, and optimising models for deployment. The released models will run on millions of square kilometres of Nearmap imagery.

Experience in applying deep learning techniques to commercial use cases and non-academic problems is highly valued. We are committed to software best practices including infrastructure as code, GitOps, CI/CD, and as much automation as makes sense. A strong background in 3D modelling is advantageous in this role.

Key Responsibilities

• Design and scope greenfield machine learning projects in collaboration with the team
• Develop and deliver end-to-end solutions to complex technical problems
• Train and optimize deep learning models using our extensive multi-temporal, multi-angle, and 3D imagery datasets
• Participate in technical discussions, code reviews, and knowledge sharing sessions

Mandatory Skills

• Programming/Tech Environments: Ability to code in scientific Python, using a Linux environment, and Git for source control
• Machine Learning: Strong grasp of machine learning fundamentals (regularisation, hyperparameter optimisation, validation methods), and recent AI advancements
• Scientific Approach: Follow the scientific method of formulating hypotheses, and applying statistical tests to validate them
• Deep Learning: Applying modern artificial neural networks to solve machine learning problem
• Tertiary Qualifications Formal education in a field related to computer science, machine learning, deep learning and AI.

Highly Desirable Skills

• Domain Knowledge – Computer Vision: Working on Machine Learning problems applied to image data
• Domain Knowledge – 3D Reconstruction: Experience with 3D computer vision, photogrammetry, structure-from-motion, or related technologies
• Software Engineering: Working on shared codebases to produce production quality code
• Cloud Computing: Working on AWS or GCP using distributed virtual machines, Docker containers, etc.
• GP-GPU: Using GPUs to accelerate scientific computing
• Scale: Working with large data sets, where data sets don't fit into memory, and require multiple nodes to compute efficiently

Personal Attributes

• Pragmatism: While extensive knowledge of ML theory is highly valued, we prioritize pragmatic solutions that work over elaborate theory when shipping products
• Collaboration: Data science is a team sport—communicate well, share knowledge, and be open to taking on ideas from anyone in the team
• Attention to detail: Thoroughness in model development, testing, and documentation

This role is based in Sydney, Australia but also open to candidates from the east coast of Australia working remotely.

Please note: Visa sponsorship is not available for this role. Applicants must have permanent
rights to work in Australia.
 

Some of our benefits

Nearmap takes a holistic approach to our employees’ emotional, physical and financial wellness. Some of our current benefits include:

• 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 (of course!)
• 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!

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

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

Thanks, but we got this! 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.