Principal RF Engineer

About This RoleAI processing…

Key Responsibilities

• 1
  Own and continuously improve TDOA, FDOA, and AoA geolocation algorithms from mathematical first principles through to working prototype implementations.
• 2
  Develop deep understanding of the existing production geolocation codebase. Identify design assumptions, performance bottlenecks, and areas where the underlying math can be strengthened.
• 3
  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.
• 4
  Develop and improve calibration approaches for timing, frequency, antenna, and geometry alignment across a multi-use distributed satellite constellation.
• 5
  Analyze geolocation outputs against ground truth and known emitter positions to identify systematic errors, performance regressions, and improvement opportunities.
• 6
  Model and characterize error sources: satellite ephemeris uncertainty, clock drift, ionospheric/tropospheric propagation effects, multipath, antenna calibration, and receiver noise.
• 7
  Incorporate orbital mechanics into signal models, accounting for satellite motion, Doppler dynamics, and constellation geometry.
• 8
  Conduct performance analysis: derive theoretical bounds, run Monte Carlo simulations, and validate against real satellite data.
• 9
  Translate validated algorithm improvements into specifications that software engineers implement in production systems. Review those implementations for correctness.
• 10
  Add new capabilities as mission requirements evolve: new measurement types, new constellation geometries, new operating conditions.
• 11
  Investigate and resolve anomalies in geolocation outputs by tracing errors back through the signal processing and estimation chain.
• 12
  Document algorithms, assumptions, and performance characteristics with sufficient rigor for defense customer technical review.

Requirements

• Advanced degree (MSc or PhD) in electrical engineering, physics, applied mathematics, aerospace engineering, or a closely related field, with thesis or research work in estimation theory, statistical signal processing, or a related discipline.
• Strong mathematical foundation in estimation and detection theory, linear algebra, probability, and optimization.
• Demonstrated ability to go from problem formulation to working code. Python proficiency required; you will prototype algorithms, run simulations, and analyze data in Python daily.
• Comfort working with imperfect real-world datasets where calibration is incomplete, truth data is sparse, and operational constraints demand pragmatic tradeoffs.
• Comfort with iterative, data-driven development: you examine outputs, form hypotheses about what is limiting performance, implement fixes, and measure the result.
• Ability to read and understand an existing algorithmic codebase built by someone else, and to work within and improve that system rather than rewrite it.
• Understanding of, or demonstrated ability to rapidly learn, RF propagation physics and the signal models underlying TDOA, FDOA, and AoA estimation.
• Familiarity with orbital mechanics concepts sufficient to incorporate satellite position and velocity into geolocation models.
• Ability to read, understand, and critically evaluate published research in signal processing and geolocation.
• Direct experience with TDOA, FDOA, AoA, or hybrid geolocation techniques.
• Background in SIGINT, electronic warfare, passive radar, or GNSS signal processing.
• Experience with SAR, InSAR, or other radar remote sensing (the estimation theory and signal processing fundamentals transfer directly).
• Experience developing or improving calibration routines for distributed RF systems.
• C++ reading proficiency sufficient to review and validate production implementations of your algorithms.
• Prior work in a defense, intelligence, or aerospace context.
• Experience with spaceborne RF systems, phased array antennas, or LEO satellite constellations.

Perks & BenefitsTypical for this role