Meta is seeking Research Interns to join our Natural Language Processing teams. These teams are part of the Facebook AI Research (FAIR) organization within Meta, working to advance the state of the art in natural language understanding and generation, and deploys these systems at scale to break down language barriers, enable people to understand and communicate with anyone, and to provide a safe experience—no matter what language they speak.The opportunities and challenges of this work are immense. Billions of people use our services to connect and communicate in their preferred language, but many of these languages lack traditional NLP resources and our systems need to be robust to the informal tone, slang and typos often found in daily communication.Our research spans multiple areas across NLP and machine learning, including deep learning/neural networks, machine translation, speech translation, natural language understanding and generation, language modeling, pretraining, low-resource NLP, question answering, dialogue, and cross-lingual and cross-domain transfer learning.We are proposing Summer, Fall, and Winter start dates. To learn more about our research, visit https://research.facebook.com.
- Perform research to advance the science and technology of intelligent machines.
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Develop novel and accurate NLP algorithms and systems, leveraging deep learning and machine learning on big data resources.
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Contribute research that can be relevant to Facebook product development.
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Currently has, or is in the process of obtaining a PhD degree in the field of Machine Learning, Artificial Intelligence, Natural Language Processing or similar
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Experience in Python, C++ or other related languages.
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Must obtain work authorization in the country of employment at the time of hire, and maintain ongoing work authorization during employment
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Experience with ML areas such as Natural Language Processing, Speech, Multimodal Reasoning & Retrieval
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Comfortable manipulating and analyzing complex, high-volume, high-dimensionality data from varying sources
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Proven track record of achieving results as demonstrated by grants, fellowships, patents, as well as first-authored publications at workshops or conferences.
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Experience communicating complex research in a clear, precise, and actionable manner
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A strong interest in theoretical and empirical research and for answering hard questions with research
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Experience with the development of enterprise-level AI, machine learning and deep learning systems, involving big data management and GPU compute
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Experience with training deep neural networks for key NLP tasks
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Intent to return to degree-program after the completion of the internship/co-op