Field Data Engineer — ML-Ready RF & Drone Tech

Droneshield; Sydney; On-site; AUD 90,000 - 130,000; Full time

Job summary

DroneShield Sydney is seeking a Field Data Engineer to deliver high-quality datasets for the ML lifecycle of its drone-detection algorithms. The role involves exposure to embedded data capture tooling, the ML lifecycle, RF mechanics, data processing, and working with some of the world's most advanced drone platforms.

The successful candidate will operate in a multi-disciplinary team, travel within Greater Sydney weekly, and engage in hands-on RF work, data analysis, and workflow improvements to

Qualifications

• BS degree in Engineering (Aerospace/Mechanical/Mechatronic)
• Experience operating a Linux terminal
• Exposure to the machine learning lifecycle and/or computer networking is a plus
• Drone enthusiast and industry trends awareness are desirable
• Hiring for junior & mid-level levels

Responsibilities

• This multi-disciplinary role sits in the Signal Intelligence Operations Team to create high-quality datasets for AI model training and algorithm development.
• Record RF data in anechoic chambers and various environments; travel to field sites within Greater Sydney at least weekly.
• Research and analyze RF signatures emitted by state-of-the-art drones; hands-on soldering and configuration of RF emitters.
• Process and organize raw data in the Linux terminal.
• Improve current data capture workflow with process and technology improvements

Skills

Linux terminal

Machine learning lifecycle

Drone enthusiasm

Soldering

Education

BS degree in Engineering (Aerospace/Mechanical/Mechatronic)

Tools

RF Emitters

Job description

DroneShield Sydney is seeking a Field Data Engineer to deliver high-quality datasets for the ML lifecycle of its drone-detection algorithms. The role involves exposure to embedded data capture tooling, the ML lifecycle, RF mechanics, data processing, and working with some of the world's most advanced drone platforms.

The successful candidate will operate in a multi-disciplinary team, travel within Greater Sydney weekly, and engage in hands-on RF work, data analysis, and workflow improvements to