We are looking for individuals who are passionate about India's defence and believe that India needs sovereignty and supremacy in the RF spectrum. If that is you, read on.

Who We Are
Kawa Space is building the deterrence stack for modern national security teams. We develop satellite-based datasets, real-time spectrum intelligence, and automated geolocation for global intelligence and national security teams.

The Role
You will work on the RF signal processing pipeline, on airborne drone-based RF situational awareness system. You will take raw IQ samples from a drone-mounted receiver and build detection, classification, and direction finding outputs under a sub-second latency budget. Strong MATLAB skills are non-negotiable. You will work directly with the track lead and deploy algorithms onto Edge Devices in the field.

What You Will Do
— Implement detection algorithms (CFAR, energy detection, matched filter) in MATLAB and Python
— Build classification pipeline for drone classes, operators, radars, and ADS-B emitters
— Prototype and validate direction finding algorithms (AoA, TDoA) in MATLAB
— Port validated algorithms to Python/C++ for Edge deployment on the drone
— Support outdoor field tests and iterate based on real-world RF data
— Work with the ML engineer on classifier integration and dataset feedback loops

What We Are Looking For
— Fresh graduate to 2 years of experience in RF/DSP or related field
— Strong MATLAB skills — you must be able to prototype, simulate, and validate algorithms in MATLAB
— Solid fundamentals in signal processing: FFT, filtering, modulation, detection theory
— Basic Python for data processing and experimentation
— Degree in ECE, EE, or related field
— Comfortable in fast-moving, outdoor, field test environments

Nice to Have
— Exposure to GNU Radio, SDR toolchains, or IQ data processing
— Any project or thesis work on drone RF signatures, SIGINT, or spectrum monitoring
— Familiarity with direction finding or geolocation algorithms
— Experience with HackRF, USRP, or similar SDR hardware