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Meta is seeking Research Interns to join Fundamental AI Research (FAIR) Multimodal Foundations teams. These teams are committed to advancing the field of Artificial Intelligence by making fundamental advances in technologies to help interact with and understand our world. Our interns have an opportunity to make core algorithmic advances and apply their ideas at an unprecedented scale. Our teams are looking for candidates with expertise in the Natural Language Processing & Multimodality domains, such as: machine translation, speech translation, natural language understanding and generation, language modeling, pretraining, low-resource NLP, question answering, dialogue, cross-lingual and cross-domain transfer learning, image/video understanding and generation, and watermarking. Our team at Meta AI offers twelve (12) to twenty-four (24) weeks long internships and we have various start dates throughout the year.
Job Responsibility:
Develop novel state-of-the-art computer vision algorithms and corresponding systems, leveraging various deep learning techniques
Based on the project, help analyze and improve efficiency, scalability, and stability of corresponding deployed algorithms
Perform research to advance the science and technology of intelligent machines
Perform research that enables learning the semantics of data (images, video, text, audio, and other modalities)
Collaborate with researchers and cross-functional partners including communicating research plans, progress, and results
Contribute research that can be applied to Meta product development
Requirements:
Currently has or is in the process of obtaining a PhD degree in Computer Science, Computer Vision, Artificial Intelligence, or relevant technical field
Must obtain work authorization in the country of employment at the time of hire and maintain ongoing work authorization during employment
Experience with Python, C++, C, Java or other related languages
Experience building systems based on machine learning and/or deep learning methods
Nice to have:
Intent to return to a degree program after the completion of the internship/co-op
Proven track record of achieving significant results as demonstrated by grants, fellowships, patents, as well as first-authored publications at leading workshops or conferences such as NeurIPS, ICML, ICLR, CVPR, ICCV, ECCV, ACL or similar
Experience working and communicating cross functionally in a team environment
Experience in advancing AI techniques in computer vision, including core contributions to open source libraries and frameworks in computer vision
Publications or experience in machine learning, AI, computer vision, optimization, computer science, statistics, applied mathematics, or data science
Experience solving analytical problems using quantitative approaches
Experience setting up ML experiments and analyze their results
Experience manipulating and analyzing complex, large scale, high-dimensionality data from varying sources
Experience in utilizing theoretical and empirical research to solve problems