Engineering Roles

RF & Sensors Algorithm Engineer / Researcher

In this role, you’ll design the algorithms that deliver overmatch in an increasingly contested spectrum. Your work—adaptive beamforming, multi-emitter localization, waveform design, RF threat emulation—moves from breakthrough idea to mathematical model to prototype to fielded hardware. You’ll help turn theory into deployed capability.

The Work
You’ll tackle signal processing problems that most defense companies leave unsolved. The spectrum is contested. Threats evolve quickly. Sensors mislead in saturated environments. You’ll develop algorithms that extract signal from noise under the constraints that matter in the real world: compute, latency, and power. Your toolkit spans radar, electronic warfare, and emerging domains where signals are the terrain. You’ll work with MATLAB, Python, and optimization libraries alongside signal processing theory: Kalman filters, Bayesian inference, and deep learning for detection and classification. Some of your work will be pure research; some will be validated against live data you can’t discuss. 

You’ll work at the seam between the RF hardware engineers who build the antenna arrays and receivers and the software team that turns your algorithms into robust, efficient code. You’ll collaborate with researchers across STR when problems span domains. When you hand off a prototype, you’ll brief the team on what it does, why it works, and where it breaks down. Sometimes, you’ll publish and defend your work through peer review. Sometimes, your highest-impact work will remain classified, because it matters.
Who You Work With
You’ll collaborate with hardware engineers who design the front-ends your algorithms optimize for and systems engineers who integrate everything into missions. You’ll have access to real lab equipment—RF chambers, acoustic test beds, prototype hardware—and you’ll work in small teams on problems with weeks-long horizons rather than multi-year program cycles.
What We Look For
A research-credible signal processing background with command of estimation and detection theory (Kalman filters, Bayesian inference, and deep learning for classification), and fluency in MATLAB and Python; an advanced degree is common.

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