Staff RF Geolocation Engineer - Passive Sensing Leader

Chaos Industries

Washington (District of Columbia)

On-site

USD 180,000 - 230,000

Full time

2 days ago

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Benefits offered by this job

Health Benefits

401k with company match

FSA

HSA

Life insurance

Free daily lunch

No meeting Fridays

Unlimited PTO

Job summary

CHAOS Industries is seeking a Staff RF Geolocation Engineer to lead the development of advanced passive RF geolocation capabilities for our electromagnetic warfare products. You will derive, implement, and validate high-performance localization solutions across distributed sensor networks, collaborating with cross-functional teams to ensure robust, real-time performance.

The role covers algorithm lifecycle from first-principles formulation to software integration, calibration, field

Qualifications

BS degree in a technical field and 5+ years in RF signal processing, estimation, or geolocation.
Strong foundation in detection theory, estimation, and linear algebra.
Experience with passive RF geolocation methods such as TDOA, FDOA, multilateration, interferometry, or hybrid localization.
Proficiency in Python, MATLAB, C++, or similar languages for modeling and implementation.
Ability to translate models into production-ready software for RF/SDR hardware.
On-site work 3–5 days per week in Hawthorne, CA or Washington, D.C. and ability to obtain security clearance.

Responsibilities

Design and derive advanced passive RF geolocation algorithms from first principles for distributed sensor networks.
Develop coherent and non-coherent passive geolocation and imaging approaches with multi-node processing.
Apply Neyman-Pearson, Bayesian, CFAR frameworks to maximize detection probability under varied conditions.
Apply maximum likelihood estimation and linear algebra to formulate robust localization solutions.
Model real-world nonidealities such as oscillator phase noise and calibration error.
Develop and refine software for passive geolocation and RF scene analysis using Python, MATLAB, C++.
Translate algorithms into real-time implementations on DSP, GPU, or accelerated architectures.
Build high-fidelity simulations to evaluate accuracy, sensitivity, and tradeoffs.
Collaborate with hardware and systems engineers to define RF front-end and timing needs.
Document assumptions, performance, and test results for stakeholders and customers.