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Applied Scientist, FAR (Frontier AI & Robotics)

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The role

Design and implement novel deep learning architectures to enable robots to perceive, reason, and act in real-world environments.
Lead independent research initiatives on robotics foundation models, focusing on perception, manipulation, and end-to-end vision-language-action systems.
Develop techniques for open-vocabulary panoptic scene understanding, multimodal LLM scaling, and sim2real/real2sim transfer.
Drive projects from concept to production, ensuring robust performance and scalable inference in dynamic settings.
Collaborate with platform and robotics teams to optimize models for real-world applications and seamless deployment.
Turn theoretical insights into practical, scalable solutions using large compute resources and real-world datasets.

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