🛠 Tech Stack

💼 About This Role

You'll own the mathematical foundations of a operational space-based RF geolocation system using TDOA, FDOA, and AoA measurements from LEO satellites. Your core impact is systematically improving estimation algorithms to deliver real customer results in a hands-on, iterative environment. This role blends deep signal processing theory with daily Python coding on real-world imperfect datasets.

🎯 What You'll Do

• Own and improve TDOA, FDOA, and AoA geolocation algorithms from first principles to prototypes.
• Analyze geolocation outputs against ground truth to identify systematic errors.
• Develop calibration approaches for timing, frequency, antenna, and geometry alignment.
• Translate validated algorithm improvements into production specifications and review implementations.

📋 Requirements

• Advanced degree (MSc/PhD) in electrical engineering, physics, applied math, or aerospace engineering.
• Strong foundation in estimation theory and statistical signal processing.
• Python proficiency for daily prototyping and data analysis.
• Ability to work 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 GNSS signal processing.
• C++ reading proficiency for reviewing production implementations.

🎁 Benefits & Perks

• 🏖️ Flexible PTO
• 💰 Equity options
• 🏥 Health insurance
• 🚀 Work with LEO satellite data

📨 Hiring Process

Estimated timeline: 2-4 weeks · AI estimate

1. 1Phone Screen· 30 min
2. 2Technical Interview· 60 min
3. 3On-site Interview· 120 min

🚩 Heads Up

• Role expects deep expertise across multiple domains (RF, orbital mechanics, estimation theory)