Machine Learning Engineer - Deep Learning Specialist (Computer Vision)

Nearmap

22h • Hybrid

About The Position

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.

Requirements

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

Nice To Haves

• Working on Machine Learning problems applied to image data
• Experience with 3D computer vision, photogrammetry, structure-from-motion, or related technologies
• Working on shared codebases to produce production quality code
• Working on AWS or GCP using distributed virtual machines, Docker containers, etc.
• Using GPUs to accelerate scientific computing
• Working with large data sets, where data sets don't fit into memory, and require multiple nodes to compute efficiently
• While extensive knowledge of ML theory is highly valued, we prioritize pragmatic solutions that work over elaborate theory when shipping products
• Data science is a team sport—communicate well, share knowledge, and be open to taking on ideas from anyone in the team
• Thoroughness in model development, testing, and documentation

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

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 (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!

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Education Level: No Education Listed
• Number of Employees: 101-250 employees