Amazon Robotics seeks an Applied Scientist to advance reinforcement learning for manipulation. You will design policies for non-prehensile, contact-rich tasks, build large-scale simulation environments, and transfer policies to physical robots.
Collaboration with control, perception, and hardware teams will be essential as you publish and present results in academia. The role emphasizes creating robust, scalable RL workloads, with production-quality code and a focus on sim-to-real transfer.
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