AI Resident - Learning From Videos (LFV)

Summary

Toyota Research Institute is focused on improving the quality of human life through advanced AI and robotics. The AI Resident will work with the Learning From Videos team to develop algorithms for multi-modal learning and contribute to research efforts in embodied AI.

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

Skills

• 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
• Application of machine learning and computer vision to embodied applications

Qualifications

Must Haves

• 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

Nice to Haves

• 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
• Application of machine learning and computer vision to embodied applications

Benefits

• TRI offers a generous benefits package including medical, dental, and vision insurance, and paid time off benefits (including holiday pay and sick time).
• Additional details regarding these benefit plans will be provided if an employee receives an offer of employment.