Senior Engineer, Radar Modeling & Simulation (Dallas/San Diego) (R4537)

Team: X-BAT Engineering - Software

Location: Dallas, Texas, San Diego, California

Commitment: Full Time Employee

Workplace Type: onsite

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. 
 

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.