AI Jobs in Munich

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The role involves training, evaluating, and monitoring new and improved LLMs and other algorithmic models. The engineer will test and deploy content moderation models in production and iterate based on real-world performance metrics and feedback loops. They are expected to develop medium to long-term vision for content understanding-related R&D, collaborating with management, product, policy & operations, and engineering teams. The position requires taking ownership of results delivered to customers, advocating for changes in approach where needed, and leading cross-functional execution.

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As an AI Tutor in Mathematics, you will generate prompts that challenge AI, define comprehensive scoring criteria to evaluate the accuracy of the AI's answers, and correct the model's responses based on your domain-specific knowledge. You will contribute to projects aligned with your skills by creating training prompts and refining model responses to help shape the future of AI and ensure technology benefits everyone.

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Developing and maintaining MCP-compatible evaluation servers, implementing logic to check agent actions against scenario definitions, creating or extending tools that writers and QAs use to test agents, working closely with infrastructure engineers to ensure compatibility, and occasionally helping with test writing or debug sessions when needed.

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As a Senior AI Research Scientist for Vision-guided robotics at Intrinsic, 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 that can be deployed 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 robotic hardware, evaluating model performance in 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 industrial problems, mentoring junior researchers, and contributing 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 enabling robots to perform complex, contact-rich manipulation tasks. You will explore the intersection of computer vision and robotic control, designing systems for robots to perceive and interact with objects in dynamic environments, creating models that integrate visual data to guide physical manipulation beyond simple grasping. Collaborating with a multidisciplinary team, you'll translate cutting-edge concepts into robust capabilities deployable on physical hardware for industrial applications. You will research and develop deep learning architectures for visual perception and sensorimotor control, design algorithms for manipulation of complex or deformable objects with high precision, collaborate with software engineers to optimize and deploy prototypes onto robotic hardware, evaluate model performance in simulations and real-world environments to ensure robustness, identify opportunities to apply advancements in computer vision and robot learning to industrial problems, and mentor junior researchers 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 by 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 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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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 involves creating models that integrate visual data to guide physical manipulation, advancing 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 robotic 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 precise manipulation of complex or deformable objects, collaborating with software engineers to optimize and deploy research prototypes on robotic hardware, evaluating model performance in simulation and real-world environments to ensure robustness, identifying opportunities to apply state-of-the-art computer vision and robot learning advancements to 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 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.