Nearmap Hiring for Senior Software Engineer (Backend, Python) Job at Sydney, Australia Full Time

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 back to 2009). We produce automated 3D models of entire cities, and have recently launched our new product, Nearmap AI, which turns our visual content into semantic information to power decisions in a wide range of organisations. As a publicly listed company focussed on growth, we have both the resources to allow you to succeed in your role, and the agility (thanks to cloud-based infrastructure) to rapidly take advantage of the latest developments in the field. Nearmap is continually evolving, and you’ll need to thrive in a fast paced environment that changes rapidly.

We are recruiting for Senior Software Engineers with a specialisation of backend and data systems tools and techniques to join teams within the AI Systems group. You’ll be designing, building, and operating software systems that take petabytes of data to transform imagery to insight. Our technology stack is based on the python scientific libraries and traverses deep learning technology such as Tensorflow and Pytorch, cloud native technology such as Kubernetes, Kubeflow and Kafka, and GIS tools such as the Shapely and GeoPandas libraries. We are committed to software best practices including infrastructure as code, GitOps, CI/CD, and as much automation as makes sense.

You will work with an incredibly passionate and talented team of Data Scientists, Machine Learning Engineers and Software & Data Engineers, and your work will interface with systems that run on Kubernetes clusters with thousands of GPUs, train large deep learning models with novel architectures, and produce sophisticated data products for a broad range of customers. The AI Systems group mixes data science, ML engineering and software engineering, and is comprised of three teams divided along responsibility lines, rather than skill sets: AI Model Systems, AI Model R&D, and AI Output Systems.

The AI Model Systems team has responsibility for building the systems and managing the data for human expert labelling of our imagery, and building the training and management systems that produce our deep learning models. We have a custom labelling environment built on our Map Browser product that allows our labelling team to annotate 2D, 3D and source imagery. We use algorithms in the loop to enhance the human labelling of millions of images, and automatically produce training data sets for ML that continually grow and improve in quality as we seek to build a richer machine learning derived picture of our physical world. We support the training of large, complex models on our multi-node GPU cluster. We are looking to build software and systems in place to facilitate efficient distributed and continual model training platform. This role will be critical in achieving that.

A typical day will look like this

• Participation in the design and scoping of greenfield projects
• Work within a team to deliver end-to-end technical solutions — typically starting with spike sessions, onto architectural design and test creation, iteration on the solution, and ultimately deploying to production.
• Commitment to software best practices and a strong culture of peer review.
• May be required to supervise associates.

Experience

We are recruiting for Software Engineering roles for the AI Model Systems team, that require solid experience with deep learning techniques and tooling. As we continue to evolve our systems, and we are looking for mid-level, to highly skilled principals with extensive industry experience. PhDs and Masters are common in the team, but by no means necessary – we’re more interested in what you can do!

Skills

We’re after exceptional candidates, who have real world experience but is still eager to learn.

Essential:

• Programming/Tech Environments: Ability to code in scientific python, using a Linux environment, and git for source control. Commitment to software engineering principles, a keen eye for clean code, and a passion for robustness and correctness.
• Software Engineering: Working on shared codebases to produce production quality code deployed in containerised environments.
• Mandatory Technical Skills:
  • Production data systems (databases, unstructured data stores, pipelines etc.)
  • Cloud technologies
  • Python (application development, not just scripting!)
  • REST APIs (and gRPC)
  • Kubernetes & Docker
  • Stream processing (ideally including Kafka)
  • Work with terabytes or petabytes of semi/unstructured data in a data warehouse or lake setup.
• Scale: Working with large data sets, where data sets don’t fit into memory, and require multiple nodes to compute efficiently.
• Scientific Approach: Follow the scientific method of formulating hypotheses, and applying statistical tests to validate them.
• Cloud Computing: Working on AWS or GCP using distributed virtual machines, Kubernetes, etc. is mandatory for some roles, beneficial for others.
• MLOps: Experience with operationalising ML applications and workflows.

Highly Desirable (mandatory for some roles, desirable for others):

• Machine Learning: A strong grasp of machine learning fundamentals.
• Deep Learning: Applying modern artificial neural networks to solve machine learning problems using GPUs.
• Experience with Pytorch and Tensorflow is nice to have for this role. Other machine learning or numerical computing experience is also desired.
• Domain Knowledge – Computer Vision: Working on Machine Learning problems applied to image data.

Personal attributes

• Pragmatism: While extensive knowledge of theory and best practices are highly valued, pragmatism wins over elaborate theory when it comes to shipping products that work.
• Collaboration: data science is a team sport, communicate well, share knowledge, and be open to taking on ideas from anyone in the team.
• Education and Experience: At minimum, a technical bachelors level degree (engineering, computer science, etc.), with a few years of experience beyond that.
• Attention to detail: Showing attention to detail when it counts is important… to be considered for this role, [click this link](https://www.dropbox.com/s/flbmgxu0sc3e9xq/test_v2.psv?dl=0) and apply some basic data science skills (an astute software engineer should be able to solve it quickly with a little googling!).

Some of our perks include…

• Competitive pay, Bonus plan and Employee Share Scheme
• Flexible working environment, work life balance is a necessity
• Opportunities for continued career growth and development
• Free reign of Nearmap’s products

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.

Watch our culture video and find out more about what a day in the life at Nearmap looks like: https://www.youtube.com/watch?v=R7rikZqa8n8

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

Watch some presentations on what we do in the AI Systems group:

https://youtu.be/WSMYfAEdAe4

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.