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.

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