Engineer building and scaling large-scale simulated environments ('worlds') in which reinforcement-learning 'superlearner' agents emerge and train at an AI research company. Day-to-day: designing, implementing, maintaining and scaling simulation infrastructure with distributed server-client architectures, physics engines, GPU-accelerated simulation (e.g. NVIDIA Warp) and low-level languages like R
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