We're looking for a Research Engineer to help expand our multimodal information processing systems for video understanding.
Machine learning for video understanding requires multimodal information. As a research engineer, you'll have the opportunity to work on projects spanning multiple machine learning topic areas, including computer vision, natural language processing, and structured knowledge graphs.
Typical activities include implementing and evaluating deep learning models, integrating features from multiple video modalities, curating datasets for novel machine learning applications, and deploying models into production. Example projects: multilingual optical character recognition, webly-supervised object detection, language modeling for speech-to-text, and knowledge graph representation learning.
We develop an end-to-end video search and understanding platform that indexes and monitors live streams, periodic video feeds, and manually uploaded video content. We work with private, public, and non-profit partners to provide solutions for a variety of large-scale video meta-analysis problems. Public applications powered by our platform include CNBC's Warren Buffet Archive, Alliance for Securing Democracy's Hamilton Dashboard for monitoring state-sponsored disinformation, and shot-list generation for the Associated Press's video footage archive.