Research Scientist Intern, FAIR - Language & Multimodal Foundations (PhD)
Location
Menlo Park, CA
Job Type
Full-time
Category
other-general
Posted
June 22, 2026
**Summary:**
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. We are seeking individuals passionate in areas such as Natural Language Processing, Audio and Speech processing, Computer Vision, Machine Learning, Deep Learning, and Reinforcement Learning. 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, computer vision, language modeling, pretraining and post-training, low-resource NLP, question answering, dialogue, cross-lingual and cross-domain transfer learning, and multimodal understanding, ...
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. We are seeking individuals passionate in areas such as Natural Language Processing, Audio and Speech processing, Computer Vision, Machine Learning, Deep Learning, and Reinforcement Learning. 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, computer vision, language modeling, pretraining and post-training, low-resource NLP, question answering, dialogue, cross-lingual and cross-domain transfer learning, and multimodal understanding, ...