Principal RF Engineer

Principal RF Engineer You will own the mathematical and physical foundations of one of the few operational commercial space-based RF geolocation systems in active customer use today. The core problem: estimating the position of RF emitters using time difference of arrival (TDOA), frequency difference of arrival (FDOA), and angle of arrival (AoA) measurements collected by a constellation of low Earth orbit (LEO) satellites. You will formulate estimation problems, develop and validate algorithms, characterize error sources, and drive performance improvements across all three measurement domains. You will inherit a working production geolocation system. This is not a greenfield research project. The algorithms exist, they run, and they produce results for real customers. Your job is to understand the existing system deeply, identify where performance is limited, and systematically improve it. Over time you will also extend the system with new measurement types and capabilities as mission requirements evolve. This is a hands-on, iterative role operating on real-world data with all its imperfections. Calibration is incomplete. Truth data is sparse. Operational constraints require pragmatic engineering tradeoffs. You will spend significant time examining real geolocation outputs, diagnosing performance issues, refining algorithms based on what the data shows, and shipping incremental improvements. The work cycle is not "design an algorithm and hand it off." It is: analyze outputs, identify the limiting error source, develop or refine an algorithmic solution, validate it against data, and repeat. You will work alongside software engineers who handle production implementation and infrastructure; your role is to ensure the algorithms are correct, well-understood, and continuously improving. You will write code daily. Python is the primary tool for prototyping, simulation, data analysis, and algorithm validation. This is not a pure research position; the expectation is that you are building, testing, and iterating on working code, not producing papers. Key Responsibilities Own and continuously improve TDOA, FDOA, and AoA geolocation algorithms from mathematical first principles through to working prototype implementations. Develop deep understanding of the existing production geolocation codebase. Identify design assumptions, performance bottlenecks, and areas where the underlying math can be strengthened. Reason across the full sensing chain: from collection geometry and onboard constraints through estimation algorithms to operational product performance. Own the end-to-end understanding of how system-level decisions affect geolocation accuracy. Develop and improve calibration approaches for timing, frequency, antenna, and geometry alignment across a multi-use distributed satellite constellation. Analyze geolocation outputs against ground truth and known emitter positions to identify systematic errors, performance regressions, and improvement opportunities. Model and characterize error sources: satellite ephemeris uncertainty, clock drift, ionospheric/tropospheric propagation effects, multipath, antenna calibration, and receiver noise. Incorporate orbital mechanics into signal models, accounting for satellite motion, Doppler dynamics, and constellation geometry. Conduct performance analysis: derive theoretical bounds, run Monte Carlo simulations, and validate against real satellite data. Translate validated algorithm improvements into specifications that software engineers implement in production systems. Review those implementations for correctness. Add new capabilities as mission requirements evolve: new measurement types, new constellation geometries, new operating conditions. Investigate and resolve anomalies in geolocation outputs by tracing errors back through the signal processing and estimation chain. Document algorithms, assumptions, and performance characteristics with sufficient rigor for defense customer te ... (truncated, view full listing at source)