RF Signals Analyst (AI)

TL;DR

RF Signals Analyst (AI): Processing real-world RF sensor data into structured ground truth for machine learning with an accent on signal characterization and maritime RF events. Focus on building high-quality labeled datasets, defining labeling taxonomies, and identifying platform noise to improve ML model performance.

Location: Hybrid (Arlington, VA; Boston, MA; San Francisco, CA)

Company

hirify.global leverages AI and robotics to enhance maritime domain awareness through distributed open-ocean systems.

What you will do

• Analyze RF event data using IQ representations, spectrograms, and PSDs to identify and tag signals of interest.
• Develop and maintain a scalable maritime RF labeling taxonomy, including signal classes and ambiguity handling.
• Create high-quality, technically defensible labeled datasets for machine learning training.
• Identify and document host vessel interference and environmental noise to support rejection libraries.
• Collaborate with DSP and ML engineers to resolve edge cases and improve labeling standards.
• Utilize contextual data such as AIS and camera imagery to support signal interpretation.

Requirements

• 3+ years of experience in RF signal analysis, SDR-based review, EW/SIGINT/ELINT, or RF dataset creation.
• Practical experience with IQ captures, spectrograms, waterfall plots, and PSDs.
• Proficiency in Linux and Python for inspecting and processing signal data.
• Experience with structured labeling, annotation, and technical review workflows.
• Must be based in or able to work from Arlington, VA, Boston, MA, or San Francisco, CA.

Nice to have

• Experience in maritime RF environments or other high-interference operational settings.
• Understanding of how label quality and taxonomy design affect downstream ML training and evaluation.
• Active Secret clearance or the ability to obtain and maintain one.