Staff Engineer, Modelling and Simulation

About the role

Shield AI is a defense-tech company whose products include Hivemind autonomy software, aircraft and simulation technologies. The Hivemind Simulation team powers the AI Factory's training and evaluation of autonomous pilots, while the Simulation Platform team builds the framework and infrastructure that lets engineers run simulators and evaluate autonomy at scale. As a Staff Software Engineer on the Simulation Platform team, you will build and integrate simulators and develop Monte Carlo infrastructure, working as an individual contributor who also drives technical direction and mentors engineers.

Key responsibilities

• Grow the simulation framework's ecosystem by integrating existing simulators and standards, and building new ones where needed
• Build reusable Monte Carlo infrastructure for parameterization, execution, reproducibility and result collection across large simulation campaigns
• Develop multithreaded and multi-process simulation capabilities, covering synchronization, timing, state exchange and performance
• Work with autonomy, GNC and RTA engineers and field operators to turn evaluation needs into simulation interfaces and infrastructure
• Support platform-specific performance validation using physics models (e.g. 6DoF, 3DoF)
• Set technical direction, lead design reviews and mentor engineers in simulation architecture and production software development

Required profile

• Typically 10 years of related experience with a Bachelor's degree, or 9 years with a Master's, or 7 years with a PhD, or equivalent
• Demonstrated experience building and running multithreaded, multiprocess real-time simulations of aircraft dynamics
• Experience developing Monte Carlo infrastructure and using it to design, run and analyze simulation campaigns
• Ability to drive technical decisions, mentor engineers and collaborate across software and domain teams
• Experience developing software or simulation under a defined V&V lifecycle

Required skills

• Strong C++ with production performance-critical software
• Preferred: Python for simulation tooling and automation
• Preferred: distributed simulation standards such as HLA, DIS and FMI/FMU
• Preferred: tools such as JSBSim, FlightGear, X-Plane, Gazebo, Isaac Sim or Simulink
• Preferred: closed-loop autonomy simulation and uncertainty modeling for Monte Carlo evaluation