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Shield AI is seeking a Staff Engineer to lead the development, tuning, and validation of trajectory prediction and aircraft recovery-behavior models. You will work with aircraft performance data, 3DOF/6DOF flyout concepts, wind effects, uncertainty bounds, and maneuver constraints to build predictive models that inform autonomous flight systems.
Key responsibilities include:
• Lead development and validation of trajectory prediction algorithms (TPA) and recovery-behavior models using real aircraft performance data and simulation frameworks.
• Build Python-based analysis, simulation, hardware-in-the-loop (HIL), and flight-test workflows to compare predicted versus observed aircraft behavior, identify model gaps, and tune parameters.
• Integrate trajectory-prediction behavior through autopilot interfaces, managing command modes, vehicle-state inputs, latency, mode transitions, control limits, and telemetry analysis.
• Support hardware integration and flight-test campaigns; evolve trajectory-prediction and safety behaviors from single-aircraft to multi-agent collaborative operations.
• Produce algorithm handoff artifacts and contribute C/C++ implementation, testing, and debugging as needed.
• Document model assumptions, validation evidence, and lead technical coordination across algorithms, software, systems, test, and platform teams.
Shield AI is a venture-backed defense-tech company developing autonomous systems and intelligent software for military and civilian applications, including Hivemind autonomy software, V-BAT and X-BAT aircraft, and Aechelon simulation technologies. The company operates globally with offices across the U.S., Europe, the Middle East, and Asia-Pacific.
REQUIREMENTS:
• Minimum 7 years of related experience with a Bachelor's degree; or 6 years with a Master's degree; or 4 years with a PhD; or equivalent work experience.
• Deep experience in trajectory prediction, aircraft-response modeling, aerospace simulation, robotics, applied autonomy, or guidance/navigation/control (GNC) domains, including 3DOF and/or 6DOF aircraft modeling.
• Expert-level Python skills for algorithm development, numerical analysis, data processing, plotting, tuning workflows, and test automation.
• Working proficiency in C or C++, with ability to read production code, debug algorithm behavior, write tests, make scoped implementation changes, and guide software engineers.
• Demonstrated experience interfacing guidance, trajectory, or safety-critical algorithms with autopilots and validating behavior through simulation, HIL, flight hardware, or flight-test data.
• Ability to document model assumptions, handoff artifacts, and validation evidence while leading technical coordination across teams.
PREFERRED:
• Experience tuning trajectory prediction, flyout, or vehicle-response models from simulation, HIL, or flight-test telemetry.
• Experience implementing or porting algorithms from Python, MATLAB/Simulink, or prototypes into C/C++ production software.
• Experience with Monte Carlo testing, scenario-based regression, validation metrics, envelope expansion, test-card planning, or flight-test safety reviews.
• Familiarity with high-reliability or safety-critical development practices (static analysis, coding standards, traceability, requirements-based testing).
• Experience with CMake, Conan, Linux, CI/CD, embedded software workflows, or production software integration.
