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This is a hands-on ML role: you will train policies, debug convergence, run experiments in simulation, and push models onto hardware - not just build the pipes around them. You'll bring deep expertise in reinforcement learning, computer vision, and supervised learning applied to robotics and embodied systems. You also need to think seriously about training infrastructure - managing GPU clusters, optimizing distributed training, and shipping models to edge devices - but the core of this role is getting in the loop with scientists and making models work. 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This is a hands-on ML role: you will train policies, debug convergence, run experiments in simulation, and push models onto hardware - not just build the pipes around them. You'll bring deep expertise in reinforcement learning, computer vision, and supervised learning applied to robotics and embodied systems. You also need to think seriously about training infrastructure - managing GPU clusters, optimizing distributed training, and shipping models to edge devices - but the core of this role is getting in the loop with scientists and making models work. 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