Job description
Nearmap is unique. An Australian global technology company with incredible people.
At Nearmap, we have tens of petabytes of high quality aerial imagery covering half a million square kilometres a year at 5-7cm resolution, and regularly captured imagery dating back to 2009. We produce automated 3D models of entire cities, and have a mature machine learning model in the market, Nearmap AI, which turns our visual content into semantic information to power decisions in a wide range of organisations. We have access to very large data-sets of roof models, post catastrophe imagery, 3D structure, a labelled data set exceeding a million images, and over 40 petabytes of geospatially registered imagery. Deep learning is foundational to our work, and we need to get very creative to get the most out of our complex data.
We are recruiting a hands-on data scientist with 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, Machine Learning Engineers and Data Engineers, and your work will have a real impact on Nearmap products. You will design novel deep learning architectures that leverage our rich data set, multiple dates of high resolution imagery, multi-angle source imagery and 3D textured mesh. You will be responsible for coming up with these novel architectures, designing training and evaluation methodologies, and producing the production deep learning models that are run at scale on our data.
Experience in applying deep learning techniques to commercial use-cases and non-academic problems is a must. 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, non-convex optimisation techniques, or multi-time processing is advantageous in this role.
You will work with an incredibly passionate and talented team of Data Scientists, Machine Learning Engineers and Data Engineers, and your work will have the potential to revolutionize 3D photogrammetry.
Nearmap is continually evolving, and you’ll need to thrive in a fast-paced environment that changes rapidly.
A typical day will look like this
- Participation in the design and scoping of greenfield projects.
- Brainstorm, implement and deliver end-to-end solutions to complex technical problems - typically starting with spike sessions, followed by the architectural design, iteration on the solution, measuring quality, and ultimately deploying to production.
- Participate in technical discussion and provide feedback.
Skills
We're after exceptional candidates, who have real-world experience and are eager to learn.
- Programming/Tech Environments: Ability to code in scientific python, using a Linux environment, and git for source control.
- Commitment to software engineering principles for scientific python, a keen eye for clean code, and a passion for robustness and correctness.
- Domain Knowledge – Computer Vision: Working on Machine Learning problems related to computer vision applications.
- Deep Learning: Applying modern artificial neural networks to solve machine learning problems using GPUs.
- A strong background in optimisation is highly desirable.
- A strong background in 3D modelling is highly desirable.
Personal attributes
- While extensive knowledge of theory and best practices are highly valued, pragmatism wins over elaborate theory when it comes to shipping products that work.
- Data science is a team sport; communicate well, share knowledge, and be open to taking on ideas from anyone in the team.
- Showing attention to detail when it counts is important; to be considered for this role, [click this link] (https://www.dropbox.com/s/u4janrzqgfxn61l/test.tar.gz?dl=0) and apply some basic data science skills (an astute software engineer should be able to solve it quickly with a little googling!).
Tertiary qualifications
Formal education in a field related to machine learning, deep learning or optimisation.
Additional Information
Some of our benefits
Nearmap takes a holistic approach to our employees’ emotional, physical and financial wellness. Some of our current benefits include competitive pay, access to the Nearmap employee share scheme, short and long-term financial incentives, flexible working options, paid volunteer days, gym and phone rebates, and lots of development opportunities including hack-a-thons and pitch-fests.
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
Please note: Successful candidate must have full working rights to work in Australia. Unfortunately, we are unable to sponsor visas for overseas candidates at this stage.
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.
