🛠 Tech Stack

💼 About This Role

You will own the mathematical foundations of Spire's operational space-based RF geolocation system, using TDOA, FDOA, and AoA measurements from LEO satellites. Your core impact is systematically improving a working production system through iterative, data-driven algorithm refinement. Unlike a research role, this is real-world work with imperfect data and pragmatic engineering tradeoffs.

🎯 What You'll Do

• Own and improve TDOA, FDOA, and AoA geolocation algorithms from first principles to working prototypes.
• Analyze geolocation outputs against ground truth to identify systematic errors and improvement opportunities.
• Model error sources including ephemeris uncertainty, clock drift, and propagation effects.
• Translate validated algorithm improvements into production implementation specifications.

📋 Requirements

• Advanced degree (MSc/PhD) in electrical engineering, physics, or applied mathematics.
• Strong foundation in estimation theory and statistical signal processing.
• Python proficiency for algorithm prototyping and data analysis.
• Comfort working with imperfect real-world datasets and iterative development.

✨ Nice to Have

• Direct experience with TDOA/FDOA/AoA geolocation techniques.
• Background in SIGINT, electronic warfare, or passive radar.
• C++ reading proficiency for production code review.

📨 Hiring Process

Estimated timeline: 2-4 weeks · AI estimate

1. 1Recruiter Call· 30 min
2. 2Technical Screen· 60 min
3. 3On-site Interview· 4 hours