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• Design and implement high-fidelity simulation environments that accurately model real-world physics and robot dynamics • Build and maintain simulation infrastructure that accelerates our AI model development cycle through: • Predictive success metrics for pre-deployment validation • Automated benchmarking systems integrated with CI/CD pipelines • Enables rapid A/B testing of model iterations • Design and implement simulation-based evaluation metrics that correlate with real-world AI model performance, including task completion rates, generalization capabilities, and robustness measures • Develop synthetic data generation pipelines that help improve model training efficiency and reduce sim-to-real gaps • Collaborate with AI, robotics, and product teams to ensure simulation environments meet real-world deployment needs
• 5+ years of engineering experience • Experience with game engines (Unity, Unreal, etc.), AR/VR/XR or physics simulators (e.g. Mujoco, IsaacSim, Drake, Pybullet, Gazebo) • Support AI research through simulation and pre-deployment validation metrics • Believe in the potential of AI to reshape industries, even if you’re new to the field. • Bonus points if you experience in a deployed robotics environment
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