JOB DESCRIPTION:
The Software Integration & Operations (SIO) group turns frontier autonomy into mission-ready aircraft. We own the commit-to-flight pipeline—deterministic aircraft and mission simulation, HIL/VIL integration, CI/CD, automated flight qualification testing, and release engineering. Our goal is simple: make AI fly—safely, repeatably, and fast.
As a Modeling & Simulation Engineer, you will be responsible for improving and adding to our world and aeronautical models so that our operator training and internal engineering pipelines have a seamless translation from sim to real results.
What You'll Do
Develop and enhance aeronautical physics models (aerodynamics, propulsion, environmental, structural, etc.) for use in simulation and evaluation.
Translate theoretical models into efficient, reliable C++ implementations with a focus on numerical accuracy and performance.
Validate models against real-world data and authoritative references, including field test data and calibration procedures.
Collaborate with simulation and training application teams to ensure models integrate cleanly into operator-facing tools.
Design automated validation and regression testing strategies for mathematical models to ensure fidelity across releases.
Prototype and evaluate new modeling techniques (reduced-order models, uncertainty quantification, machine learning–based surrogates) to push the state of the art.
Document assumptions, equations, and validation results so that both engineers and operators can trust model outputs.
Required Qualifications
BS or higher in Aerospace Engineering, Applied Math, Physics, or related field with 1+ years of aerospace modeling experience.
C++ foundation with experience implementing numerical methods.
Demonstrated experience with aerospace models such as: Aerodynamics (lift/drag curves, stability derivatives, dynamic response), Atmosphere/environment (COESA, ICAO, gravity, wind models), Vehicle dynamics.
Preferred Qualifications
1+ years of experience working on pilot/operator training systems.
Experience with Eigen or SciPy for model prototyping and validation.
Familiarity with state estimation sensor models (GPS, IMU, Gyro, etc) for simulation environments.
Background in multi-body dynamics or flight mechanics
Knowledge of uncertainty quantification and statistical analysis methods.
Strong problem-solving mindset with a collaborative and detail-oriented approach.
Familiarity with Python for test automation and data analysis pipelines.
Passion for aerospace and autonomous vehicle systems.
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