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Applied scientist - multimodal foundation models & robotics

Zürich
Microsoft Schweiz
Model
Inserat online seit: 29 April
Beschreibung

Overview The Spatial AI Lab is part of the Applied Sciences Group, a Microsoft research and development organization dedicated to creating next-generation human-computer interaction technologies leveraging the most recent AI developments and exploring new hardware capabilities and device form-factors. Our team of scientists and engineers has strong expertise in computer vision and multi-modal AI, with a particular focus on spatial and embodied AI.
As a
Scientist - Multimodal Foundation Models & Robotics on our growing team, you will conduct research at the intersection of large-scale generative modeling and embodied AI, with a focus on robotics. Your primary focus will be on building the core intelligence for a new generation of agents, training the multimodal foundation models that empower them to perceive complex environments, reason about tasks, and act seamlessly across both the physical and digital worlds. This opportunity will allow you to deepen your expertise in training embodied foundation models, deploying algorithms on robotic hardware and large-scale AI systems, and contribute to our pioneering research through publications and collaborations with partners like ETH Zurich.
Microsoft’s mission is to empower every person and every organization on the planet to achieve more. As employees we come together with a growth mindset, innovate to empower others, and collaborate to realize our shared goals. Each day we build on our values of respect, integrity, and accountability to create a culture of inclusion where everyone can thrive at work and beyond.
Responsibilities
Design and implement novel foundation models and algorithms for general-purpose embodied agents; Implement high-performance machine-learning pipelines and optimize data and learning stacks for scalability, efficiency, and performance. Optimize and deploy AI models on robot hardware; Collaborate across Microsoft research and engineering teams to transition cutting-edge re

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