3 days ago
Base Salary
$200k - $300k/yr
Responsibilities
- Lead development, tuning, and validation of TPA and recovery-behavior models using aircraft performance data, 3DOF/6DOF concepts, wind effects, uncertainty bounds, and maneuver constraints.
- Build Python-based analysis, simulation, HIL, flight-test, and regression workflows to evaluate aircraft behavior and tune model parameters.
- Integrate and evaluate trajectory-prediction behavior through custom or off-the-shelf autopilot interfaces, including command modes, vehicle-state inputs, latency, transitions, control limits, and telemetry.
- Support hardware integration and flight-test campaigns and help evolve trajectory and safety behaviors toward multi-agent collaborative CONOPS.
- Produce algorithm handoff artifacts and contribute scoped C/C++ implementation, testing, debugging, and technical guidance to software engineers.
- Coordinate technical work across algorithms, software, systems, test, and platform teams.
Requirements
- Minimum experience is 7 years with a bachelor’s degree, 6 years with a master’s degree, 4 years with a PhD, or equivalent work experience.
- Deep experience in trajectory prediction, aircraft-response modeling, aerospace simulation, robotics, applied autonomy, or GNC-adjacent domains, including 3DOF and/or 6DOF aircraft modeling.
- Expert Python skills for algorithm development, numerical analysis, data processing, plotting, tuning workflows, and test automation.
- Working proficiency in C or C++ for reading production code, debugging algorithms, writing tests, making scoped changes, and guiding software engineers.
- 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 assumptions, handoff artifacts, and validation evidence while leading cross-functional technical coordination.
- Preferred experience includes MATLAB/Simulink-to-C/C++ algorithm implementation, Monte Carlo testing, scenario-based regression, validation metrics, envelope expansion, test-card planning, flight-test safety reviews, and safety-critical development practices.
- Preferred familiarity includes static analysis, coding standards, traceability, requirements-based testing, verification evidence, CMake, Conan, Linux, CI/CD, embedded software workflows, and production software integration.
Benefits
- Full-time regular employees receive pay within the listed range, bonus, benefits, and equity.
- Temporary employees receive pay within the listed range and a temporary benefits package applicable after 60 days of employment.
- Offers are contingent on a cleared background and possible reference check.
- Military fellows and part-time employees are not eligible for benefits.
About Shield AI
Shield AI builds autonomous systems for military and national security customers, combining its Hivemind autonomy software with V-BAT and X-BAT unmanned aircraft and Aechelon simulation technologies. The privately held company sells hardware, software, and related services to U.S. and allied defense agencies. Founded in 2015 and headquartered in San Diego, it operates across the U.S., Europe, the Middle East, and Asia-Pacific, and its technology is used in operational deployments.