Senior Simulation Engineer

• Build a visually realistic simulator to test full end-to-end autonomy stack behavior, from simulating sensors to motion planning, across a range of scenario conditions. • Prototype and integrate with internal and third-party simulators to evaluate their ability to support learned system testing. • Curate scenarios, system introspection. • Build data logging frameworks used during large-scale virtual tests. • Collaborate closely with autonomy, ML, and integration teams to define simulation entry points, runtime configs, and closed-loop evaluation metrics. • Build diagnostic tooling and analysis pipelines to understand and improve real system behavior in simulation. • Lead cross-functional efforts to close the gap between simulation and on-vehicle deployment, increasing the reliability of sim-based validation. • Provide technical mentorship and foster a collaborative, high-trust engineering culture across organizational boundaries. • Demonstrate excellent design practices; generate technical documentation; lead technical presentations; aligning with stakeholders before, during, and after implementation is essential.

• Bachelor’s or Master’s in Computer Science, Robotics, or a related field. • 10+ years of experience in robotics, autonomous systems, or simulation. • Experience with 3D reconstruction (e.g. Gaussian Splatting, Neural radiance fields, etc). • Experience with 3D generation. • Experience with Unreal Engine. • Strong programming skills in Python and C++, especially for robotics or systems development. • Experience with simulation platforms (e.g., CARLA, Applied Intuition, Nvidia DriveSim, etc) and their integration into autonomous system workflows. • Knowledge of sensor simulation principles and how perception systems interact with synthetic data. • Understanding of end-to-end autonomy pipelines, from raw sensor input to trajectory outputs. • Demonstrated ability to design for both users (e.g., autonomy developers) and simulation infrastructure stakeholders. • Passion for using simulation to drive real-world progress and system understanding. • Hands-on experience validating machine learning-based autonomy stacks in closed-loop simulation. • Knowledge of scenario generation, rare event simulation, or counterfactual testing. • Knowledge of one or more cloud compute platforms, such as AWS. • Experience with multi-agent simulation or high-fidelity 3D environments. • Prior experience in fast-paced R&D environments bridging research and production.