Founded in 2015, Shield AI is a venture-backed defense-tech company with the mission of protecting service members and civilians with intelligent systems. Its products include Hivemind autonomy software and V-BAT and X-BAT aircraft. With offices and facilities across the U.S., Europe, the Middle East, and Asia-Pacific, Shield AI’s technology actively supports operations worldwide. For more information, visit www.shield.ai. Follow Shield AI on LinkedIn, X, Instagram, and YouTube.
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 sensor and communications model suite so that our operator training and internal engineering pipelines have a seamless translation from sim to real results.
#LI-SM1
Full-time regular employee offer package:
Pay within range listed + Bonus + Benefits + Equity
Temporary employee offer package:
Pay within range listed above + temporary benefits package (applicable after 60 days of employment)
Salary compensation is influenced by a wide array of factors including but not limited to skill set, level of experience, licenses and certifications, and specific work location. All offers are contingent on a cleared background and possible reference check. Military fellows and part-time employees are not eligible for benefits. Please speak to your talent acquisition representative for more information.
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Shield AI is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, marital status, disability, gender identity or Veteran status. If you have a disability or special need that requires accommodation, please let us know.
What You'll Do
Develop and enhance radar sensor models for use in simulation and evaluation of aeronautical vehicles.
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 5+ years of aerospace modeling experience.
C++ foundation with experience implementing numerical methods.
Demonstrated experience with aerospace models such as: Radar sensors, Radio communications systems
Experience validating simulations against real-world or experimental data.
Ability to write clear documentation explaining assumptions, limitations, and expected behaviors of models.
Ability to obtain a S//SAR level security clearance desired.
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.
Demonstrated experience with payload sensor models including: Laser senros, IR and optical cameras
Knowledge of uncertainty quantification and statistical analysis methods.
Experience with parallelization or GPU acceleration for compute-heavy models.
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.