UUV Simulation Engineer

# UUV Simulation Engineer We are based in Los Angeles. I would highly, highly prefer someone in LA. You will need to occasionally come onsite. We are looking for an experienced simulation engineer to build a simulation environment for an unmanned underwater vehicle (UUV). The simulation will be used to support vehicle development, autonomy testing, and validation before at-sea testing. It should represent the vehicle's movement through water, relevant environmental conditions, and the sensors used by the vehicle. ## Responsibilities * Build and maintain a simulation environment for a UUV. * Develop a vehicle dynamics and underwater environment model. * Simulate relevant navigation and perception sensors. * Integrate the simulation with our existing PX4 and ROS 2 software. * Support software-in-the-loop and hardware-in-the-loop testing. * Create tools for repeatable testing across different operating conditions. * Use real-world test data to improve the simulation over time. * Work with the engineering team to ensure the simulation supports vehicle and autonomy development. ## Qualifications * Experience developing physics-based simulations for robotic, marine, aerospace, automotive, or autonomous systems. * Strong C++ and Python development skills. * Experience with simulation platforms such as Gazebo, Isaac Sim, MuJoCo, Unity, Unreal, or similar tools. * Understanding of vehicle dynamics, coordinate frames, numerical simulation, and sensor modeling. * Experience integrating simulations with robotics or embedded software. * Familiarity with PX4, ROS 2, or similar systems. * Ability to independently design, build, document, and deliver a simulation that other engineers can use. * U.S. Person as defined by ITAR (22 CFR §120.62). ## Preferred Qualifications * Experience with underwater or surface vehicles. * Experience modeling navigation, sonar, acoustic, or environmental sensors. * Familiarity with software-in-the-loop or hardware-in-the-loop testing. * Experience validating simulations against real-world test data.