Senior Navigation Engineer - Orbit Determination & Ephemeris

The Role

STARBIRD.AI develops positioning, navigation, and timing (PNT) technology for defense and civilian markets, for environments where GNSS cannot be relied upon.

We are looking for a Senior Navigation Engineer to lead the orbital and ephemeris domain inside our navigation R&D group. You will join a navigation team with strong depth in estimation, filtering, multi-sensor fusion, and DSP, and you will own the orbital domain alongside them, setting its technical direction.

Why this role is worth your time?
This is frontier work. Alternative PNT is one of the fastest moving areas in navigation today. Driven by urgent operational need, not only academic curiosity-and the orbital domain is among its most demanding parts.

You will build technology that does not yet have a textbook and own a domain rather than inherit one. We discuss the specifics of our approach with candidates in interview.

What You'll Do

• Satellite state and orbit determination - Own the satellite state products our navigation solution consumes: position, velocity, and clock/frequency estimates with realistic, defensible uncertainties. Develop and tune the orbit determination pipelines behind them.
• Orbit modeling - Model orbital dynamics and perturbations, handle maneuvers and orbital events, and own correctness of reference frames and time systems.
• Clock and frequency - Characterize and model satellite clock, oscillator, and frequency-stability behaviour.
• Data and validation - Design and own the multi-source data layer the navigation solution depends on — ingestion, validation, versioning — and the evaluation harness behind it. Validate through simulation, recorded-data replay, and live-sky and field campaigns.
• Applied ML - Apply machine learning and data-driven methods on top of a physics-based baseline, where they measurably beat it.
• Technical direction - Translate requirements into a prioritized research plan, and grow the team's depth in this domain.

Requirements

• Sc. or Ph.D. in Aerospace Engineering, Electrical Engineering, Geodesy/Geomatics, Applied Mathematics, or Physics.
• 4+ years of hands-on experience in at least one of: orbit determination, astrodynamics/flight dynamics, GNSS/PNT algorithms, or satellite navigation.
• Strong orbital mechanics foundation: perturbation models, propagators and integrators, reference frames, and time systems.
• Statistical estimation: Kalman filtering (EKF/UKF) and/or batch least squares, plus covariance and residual analysis.
• Strong programming in Python, plus C++ or MATLAB.
• Demonstrated experience working with real measurement data-not simulation only. Comfortable with messy data, large datasets, cleaning, and validation.
• Ability to translate mathematical concepts into robust, testable, production-grade algorithms.
• Ability to take an open-ended technical problem and structure it into a work plan.

Advantages

Domain experience

• GNSS, LEO-PNT, or alternative-PNT systems.
• Navigation in GNSS-denied, degraded, or contested environments.
• Precise point positioning, carrier-phase, or Doppler processing.
• Multi-constellation and multi-frequency processing.
  

Tools and formats

• Orbit and analysis tooling: Orekit, GMAT, STK, FreeFlyer, GIPSY, Bernese, or equivalent.
• GNSS data formats: RINEX, SP3, RTCM.

Data and ML

• Machine learning applied to estimation, signal, or physical-modeling problems
• Data engineering practice for measurement data: pipelines, dataset versioning, experiment tracking.

Background

• Defense, aerospace, space, or autonomous-platform industry experience.
• Peer-reviewed publications in navigation or astrodynamics venues (ION GNSS+, NAVIGATION, AIAA/AAS, or similar).
• Experience mentoring engineers or leading a small technical workstream.