AI Resident - Learning From Videos (LFV)

Job description

Job responsibilities

• Develop, integrate, and deploy algorithms for Multi-Modal and 4D reasoning targeting physical applications.
• Handle the ingestion of large-scale datasets for training, including streaming, online, and continual learning.
• Contribute innovative solutions at the intersection of machine learning, computer vision, and robotics to improve real-world task performance.
• Work closely with robotics and machine learning researchers and engineers to understand theoretical and practical needs.
• Follow best practices producing maintainable code, both for internal use as well as for open-sourcing to the scientific community.
• Contribute to research publications and technical reports.

Job requirements

• Bachelor's or Master’s degree in Computer Science, Electrical Engineering, Robotics, or a related technical field.
• Exceptional candidates with equivalent research experience (e.g., strong publication record, open-source contributions, or industry research experience) are encouraged to apply.
• Strong background in computer vision and its applications to robotics and embodied systems.
• Demonstrated research experience through publications, technical projects, or open-source contributions.
• Strong communication skills and a collaborative mindset, with the ability to learn quickly and contribute to team research efforts.
• Passionate about assisting and amplifying older adults and those in need through dexterous manipulation, human-robot collaboration, and physical assistance innovation.
• Spatio-temporal (4D) computer vision, including multi-view geometry, 3D/4D reconstruction, video generation, self-supervised learning, occlusion reasoning, etc.
• Large-scale training of multi-modal deep learning methods, both in terms of dataset sizes and model complexity, context length extension, and efficient attention, distributed computing, etc.