Senior EW Direction Finding & Estimation Engineer (All Genders)

YOUR MISSION

You will turn our directional mesh network into a sensor. Using the same aperture that carries traffic, you will build direction finding, spectrum sensing, and GNSS-free position estimation, and prove their accuracy in the field against surveyed references. You own the error budget and the evidence, from IQ samples up to a validated position.

ABOUT THE TEAM

STARK's Electronic Warfare team is a systems-focussed engineering group delivering software-defined, mass-scalable RF solutions for autonomous systems. Combining deep domain expertise in hardware board design, thermal/ structural packaging, real-time C++ signal processing, and resilient directional mesh networking, we rapidly build field advanced EW capabilities designed to survive and operate in contested spectrum environments. 

WHAT YOU WILL DO AT STARK

• Build position estimation from the mesh itself under GNSS denial: TDOA/TOA ranging, multilateration, geometry and GDOP, the clock-synchronisation error budget, and fusion with platform navigation.
• Develop the DF and baseline spectrum-sensing chain on the directional aperture that carries traffic, running concurrently with communications.
• Own antenna calibration together with the antenna team, and keep it valid in the field.
• Own the error budget, design validation campaigns against surveyed references, and produce the evidence packs for programme milestones.

WHAT YOU BRING TO THE MISSION

• You have measured DF accuracy against real signals and done localisation with an explicit geometry and error budget. Practical experience is what counts here, not GNSS integration or theory alone.
• You have run measurement campaigns validated against a surveyed reference.
• You have calibrated an antenna array yourself.
• You work comfortably from IQ data and channel-level observables upward.

NICE TO HAVE

• A background in direction finding, radar, or SIGINT, whether from industry, a research institute, or space-based SIGINT.
• Publications with a real measurement section.
• Kalman filter or factor-graph estimation.