We’re currently looking for a developer to help us to rid New Zealand of invasive predators. We're a small team with big ambitions. This is challenging, varied and fun role - you can expect to be dealing with embedded, backend and frontend systems using a variety of technologies and languages. There's scope for machine learning and computer vision work too if that interests you.
We’re happy to consider junior, intermediate or senior candidates. Finding someone who fits the project well is more important to us than years of experience. The role is permanent and home based (we have no office). Candidates must be based in Christchurch, New Zealand and must be able to legally work in New Zealand.
Candidates should have the following essential skills and attributes:
- At least 2 years experience working as a professional software developer or a proven track record of open source software contributions.
- A working knowledge of the Linux command line.
- A working knowledge of Git and Github.
- An ability to learn and adapt to new technologies quickly.
- An ability to be work in a motivated, self-directed manner from home.
- A willingness to help out with any aspect of the project whether it be writing software, performing code reviews, system administration, documentation or community building.
- An understanding of open source development practices and processes.
Experience with any of the following areas are highly desirable:
- Automated unit and system testing
- Node.js development
- Embedded systems and Raspberry Pi
- Android development
- Linux devops & system administration
The Cacophony Project brings a technological approach to the problem of New Zealand's invasive predators which are having a major impact on native bird populations. The project has two high-level aspects:
- Technology to record and analyse birdsong at scale. Birdsong can be used as an indicator of bird population growth or decline and work is also underway to use recordings to identify particular bird species.
- A device which uses audio lures, thermal imaging and machine learning techniques to automatically attract, identify and ultimately eliminate invasive predators.
We believe our approach has the potential to be vastly more effective than the measures currently in use to manage invasive predators.
The project is being run in a completely open source manner. Anyone is able to see what we're doing, contribute improvements or build something else from it. We have a core team of full time engineers and numerous external contributors and advisors.
Send an introduction and your CV to firstname.lastname@example.org. Be sure to highlight any relevant open source contributions.