Machine Learning Engineer

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.

Skills

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.

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.

Personal attributes

• 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.

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!

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 a year as your "YOU" days
• Access to LinkedIn Learning
• Team Hackathons and Pitch-fests
• Wellbeing and technology allowance
• Annual flu vaccinations
• Nearmap subscription (of course!)
• Stocked kitchen with access to all the sustenance 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.
Watch some of our videos and find out more about what a day in the life at Nearmap looks like.

https://youtu.be/WSMYfAEdAe4

https://youtu.be/ZEGdSLWdrH0

https://youtu.be/JuHBJk2uuD8

https://youtu.be/8mSSG6uICW0

To hear an interview with Brett Tully, Director of AI Output Systems on the Super Data Science podcast, click this link: https://www.superdatascience.com/533

Mapscaping podcast: https://mapscaping.com/blogs/the-mapscaping-podcast/collecting-and-processing-aerial-imagery-at-scale

Read the product documentation for Nearmap AI:https://docs.nearmap.com/display/ND/NEARMAP+AI

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.

Thanks, but we got this! 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.