AI Resident - Learning From Videos (LFV) at Toyota… · Los Altos

Summary: Toyota Research Institute (TRI) is on a mission to improve the quality of human life through advanced research in AI and robotics. They are seeking an AI Resident to join the Learning From Videos (LFV) team, focusing on developing foundation models for multi-modal data to enhance task performance in embodied AI applications. 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 Required Qualifications: - 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 Preferred Qualifications: - 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 Required Skills: Computer Vision, Multi-Modal Learning, 4D Reconstruction Important Skills: Robotics, Machine Learning Nice-to-Have Skills: Research Experience, Collaborative Mindset Benefits: Medical, Dental, Vision insurance, Paid time off benefits, Holiday pay, Sick time