Senior Machine Learning Engineer

Company Description

Kindly note, we will be processing direct applications from the week beginning 15th April. We appreciate your time!

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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.

This role is all about translating R&D from other parts of the Nearmap AI & Computer Vision team into data and ultimately, answers. You will be working closely with a team of Data Scientists and ML Engineers to rapidly iterate on new ML-driven geospatial analytics products. You’ll be doing a mix of algorithmic implementation and validation as part of a full software engineering lifecycle. The team focusses on algorithmic systems, where each node of the computational graph is a software application in its own right (such as a deep learning model or geospatial algorithm), and the goal is to produce outstanding high quality data for customers in a fully automated and cost effective manner.

We design, build, and operate software systems that take petabytes of data to transform aerial imagery to insight. Our technology stack is based on the python scientific libraries and traverses machine vision deep learning technology such as Pytorch, and GIS tools such as the GEOS, Shapely and GeoPandas libraries. We work mostly in python for speed of development and occasionally drop down to compiled libraries when we need to care about performance.

As a well funded company focussed on growth, we have both the resources to allow you to succeed in your role, and the agility to take advantage of the latest developments in the field. Nearmap is continually evolving, and you’ll need to thrive in an environment that changes rapidly.

A typical day will look like this

• 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, measuring quality and ultimately deploying to production.
• Participation in the design and scoping of greenfield projects
• Commitment to software best practices and a strong culture of peer review.

Job Description

Skills and experience:

We're after exceptional candidates, who have real world experience but are eager to learn. 

Essential:

• Demonstrated history working in a numerical field: e.g. computer vision, applied maths, physical sciences, geospatial analysis.
• Strong approach to systems thinking, whilst remaining pragmatic
• Commitment to software engineering principles for scientific python, a keen eye for clean code, and a passion for robustness and correctness.
• Working on shared codebases to produce production quality code.
• Data science is a team sport; communicate well, share knowledge, and be open to taking on ideas from anyone in the team.
• While extensive knowledge of theory and best practices are highly valued, pragmatism wins over elaborate theory when it comes to shipping products that work.

Highly Desirable:

• Working with large data sets, where data doesn’t fit into memory, and requires multiple nodes to compute efficiently.
• A scientific mindset of formulating hypotheses, and applying statistical tests to validate them.
• Working in a cloud-native environment using highly scalable compute.
• Experience with operationalizing numerical applications and workflows.

Qualifications

Formal education in a field related to numerical science (Bachelor’s degree in computer science, engineering, statistics, physics, etc.). Applicants with a Masters/PhD will fit in well within the team, but are by no means necessary — we’re more interested in what you can do!

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:

• 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!

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:

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