AI Robotics Engineer Jobs

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As a Senior AI Research Scientist for Vision-guided robotics, you will lead the research and development of novel deep learning algorithms that enable robots to perform complex, contact-rich manipulation tasks. Your work involves exploring the intersection of computer vision and robotic control to design systems that allow robots to perceive and interact with objects in dynamic environments. You will create models that integrate visual data to guide physical manipulation, advancing beyond simple grasping to sophisticated handling of diverse items. Collaboration with a multidisciplinary team of engineers and researchers is required to translate cutting-edge concepts into robust capabilities deployable on physical hardware for industrial applications. Responsibilities include researching and developing deep learning architectures for visual perception and sensorimotor control in contact-rich scenarios, designing algorithms for manipulation of complex or deformable objects with high precision, collaborating with software engineers to optimize and deploy research prototypes onto robotic hardware, evaluating model performance in simulation and real-world settings to ensure robustness, identifying opportunities to apply state-of-the-art computer vision and robot learning advancements to practical industrial problems, mentoring junior researchers, and contributing to the technical direction of the manipulation research roadmap.

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Lead the research and development of novel deep learning algorithms that enable robots to perform complex, contact-rich manipulation tasks. Explore the intersection of computer vision and robotic control, designing systems that allow robots to perceive and interact with objects in dynamic environments. Create models that integrate visual data to guide physical manipulation, moving beyond simple grasping to sophisticated handling of diverse items. Collaborate with a multidisciplinary team of engineers and researchers to translate cutting-edge concepts into robust capabilities deployable on physical hardware for industrial applications. Research and develop deep learning architectures for visual perception and sensorimotor control in contact-rich scenarios. Design algorithms for robots to manipulate complex or deformable objects with high precision. Collaborate with software engineers to optimize and deploy research prototypes onto physical robotic hardware. Evaluate model performance in both simulation and real-world environments to ensure robustness and reliability. Identify opportunities to apply state-of-the-art advancements in computer vision and robot learning to practical industrial problems. Mentor junior researchers and contribute to the technical direction of the manipulation research roadmap.

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Lead the research and development of novel deep learning algorithms for visual perception and sensorimotor control in contact-rich robotic manipulation tasks, including designing systems that integrate visual data to guide physical manipulation beyond simple grasping. Collaborate with software engineers to optimize and deploy research prototypes onto physical robotic hardware, evaluate model performance in simulation and real-world environments for robustness and reliability, and identify opportunities to apply state-of-the-art computer vision and robot learning advancements to practical industrial problems. Mentor junior researchers and contribute to the technical direction of the manipulation research roadmap.

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As a Senior AI Research Scientist for Vision-guided robotics, you will lead the research and development of novel deep learning algorithms that enable robots to perform complex, contact-rich manipulation tasks. You will explore the intersection of computer vision and robotic control, designing systems that allow robots to perceive and interact with objects in dynamic environments. Your work will involve creating models that integrate visual data to guide physical manipulation, moving beyond simple grasping to sophisticated handling of diverse items. You will collaborate with a multidisciplinary team of engineers and researchers to translate cutting-edge concepts into robust capabilities deployable on physical hardware for industrial applications. Responsibilities include researching and developing deep learning architectures for visual perception and sensorimotor control in contact-rich scenarios, designing algorithms for robots to manipulate complex or deformable objects with high precision, collaborating with software engineers to optimize and deploy research prototypes onto physical robotic hardware, evaluating model performance in both simulation and real-world environments to ensure robustness and reliability, identifying opportunities to apply state-of-the-art advancements in computer vision and robot learning to practical industrial problems, mentoring junior researchers, and contributing to the technical direction of the manipulation research roadmap.

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Lead the research and development of novel deep learning algorithms that enable robots to perform complex, contact-rich manipulation tasks. Explore the intersection of computer vision and robotic control, designing systems that allow robots to perceive and interact with objects in dynamic environments. Create models that integrate visual data to guide physical manipulation, moving beyond simple grasping to sophisticated handling of diverse items. Collaborate with a multidisciplinary team to translate cutting-edge concepts into robust capabilities deployable on physical hardware for industrial applications. Research and develop deep learning architectures for visual perception and sensorimotor control in contact-rich scenarios. Design algorithms enabling robots to manipulate complex or deformable objects with high precision. Collaborate with software engineers to optimize and deploy research prototypes onto physical robotic hardware. Evaluate model performance in simulation and real-world environments to ensure robustness and reliability. Identify opportunities to apply state-of-the-art advancements in computer vision and robot learning to practical industrial problems. Mentor junior researchers and contribute to the technical direction of the manipulation research roadmap.

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Lead the research and development of novel deep learning algorithms enabling robots to perform complex, contact-rich manipulation tasks, exploring the intersection of computer vision and robotic control. Design systems allowing robots to perceive and interact with objects in dynamic environments, integrating visual data to guide physical manipulation beyond simple grasping to sophisticated handling. Collaborate with a multidisciplinary team to translate concepts into capabilities deployable on physical hardware for industrial applications. Research and develop deep learning architectures for visual perception and sensorimotor control in contact-rich scenarios. Design algorithms for robots to manipulate complex or deformable objects with high precision. Collaborate with software engineers to optimize and deploy research prototypes on physical robotic hardware. Evaluate model performance in simulated and real-world environments to ensure robustness. Identify opportunities to apply state-of-the-art advancements in computer vision and robot learning to industrial problems. Mentor junior researchers and contribute to technical direction for the manipulation research roadmap.

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Lead the research and development of novel deep learning algorithms that enable robots to perform complex, contact-rich manipulation tasks. Explore the intersection of computer vision and robotic control, designing systems that allow robots to perceive and interact with objects in dynamic environments. Create models that integrate visual data to guide physical manipulation, moving beyond simple grasping to sophisticated handling of diverse items. Collaborate with a multidisciplinary team of engineers and researchers to translate cutting-edge concepts into robust capabilities that can be deployed on physical hardware for industrial applications. Research and develop deep learning architectures for visual perception and sensorimotor control in contact-rich scenarios. Design algorithms that enable robots to manipulate complex or deformable objects with high precision. Collaborate with software engineers to optimize and deploy research prototypes onto physical robotic hardware. Evaluate model performance in both simulation and real-world environments to ensure robustness and reliability. Identify opportunities to apply state-of-the-art advancements in computer vision and robot learning to practical industrial problems. Mentor junior researchers and contribute to the technical direction of the manipulation research roadmap.

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Design, deploy, and maintain Figure's training clusters. Architect and maintain scalable deep learning frameworks for training on massive robot datasets. Work together with AI researchers to implement training of new model architectures at a large scale. Implement distributed training and parallelization strategies to reduce model development cycles. Implement tooling for data processing, model experimentation, and continuous integration.

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Lead the research and development of novel deep learning algorithms that enable robots to perform complex, contact-rich manipulation tasks. Explore the intersection of computer vision and robotic control, designing systems that allow robots to perceive and interact with objects in dynamic environments. Create models that integrate visual data to guide physical manipulation, moving beyond simple grasping to sophisticated handling of diverse items. Collaborate with a multidisciplinary team of engineers and researchers to translate cutting-edge concepts into robust capabilities deployable on physical hardware for industrial applications. Research and develop deep learning architectures for visual perception and sensorimotor control in contact-rich scenarios. Design algorithms enabling robots to manipulate complex or deformable objects with high precision. Collaborate with software engineers to optimize and deploy research prototypes onto physical robotic hardware. Evaluate model performance in both simulation and real-world environments to ensure robustness and reliability. Identify opportunities to apply state-of-the-art advancements in computer vision and robot learning to practical industrial problems. Mentor junior researchers and contribute to the technical direction of the manipulation research roadmap.

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Research and develop novel deep learning architectures for visual perception and sensorimotor control in contact-rich scenarios. Design algorithms that enable robots to manipulate complex or deformable objects with high precision. Collaborate with software engineers to optimize and deploy research prototypes onto physical robotic hardware. Evaluate model performance in both simulation and real-world environments to ensure robustness and reliability. Identify opportunities to apply state-of-the-art advancements in computer vision and robot learning to practical industrial problems. Mentor junior researchers and contribute to the technical direction of the manipulation research roadmap.