Machine Learning Engineer

Company Description Nearmap is the Australian-founded, global tech pioneer innovating in location intelligence. 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 liveable world. Job Description 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 optimise deep learning models using our extensive multi‑temporal, multi‑angle, and 3D imagery datasets Participate in technical discussions, code reviews, and knowledge sharing sessions Qualifications 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. Additional Information Some of our 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 (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 Nearmap takes a holistic approach to our employees’ emotional, physical and financial wellness. Some of our current benefits include: 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: For a deep dive into Nearmap AI, listen to AI Systems Senior Director Mike Bewley on the Mapscaping podcast #J-18808-Ljbffr