Research Scientist Intern, Comms & Language (PhD) Language Research Scientist

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, Reinforcement Learning or Watermarking. 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. To learn more about our research, visit https://research.facebook.com.Research Scientist Intern, Comms & Language (PhD) Language Research Scientist Responsibilities

• 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.
• 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
• 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
• Experience with deep learning frameworks

Minimum QualificationsPreferred QualificationsAbout Meta Meta builds technologies that help people connect, find communities, and grow businesses. When Facebook launched in 2004, it changed the way people connect. Apps like Messenger, Instagram and WhatsApp further empowered billions around the world. Now, Meta is moving beyond 2D screens toward immersive experiences like augmented and virtual reality to help build the next evolution in social technology. People who choose to build their careers by building with us at Meta help shape a future that will take us beyond what digital connection makes possible today—beyond the constraints of screens, the limits of distance, and even the rules of physics.


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