Research Scientist Intern, AI Research - Speech & Audio; PhD
Listed on 2026-11-02
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Research/Development
Data Scientist, AI Business & Operations
Meta AI is currently seeking Research Scientist interns. Our team creates spoken language technology to make it faster and easier for people to build community and connect with others around the world. We conduct product-motivated research in ML/AI and design, develop and deploy state-of-the-art algorithms to the rest of Meta. We work in all aspects of AI for speech and audio processing, with a primary focus on speech with large language models (LLM) to power various speech-LLM-based products.
As a Research Scientist Intern, you will help us develop innovative models and algorithms and apply them to large-scale production speech tasks.
Our teams at Meta AI offer twelve (12) to twenty-four (24) weeks long internships and we have various start dates throughout the year.
- Currently has, or is in the process of obtaining a PhD degree in the field of Computer Science, Artificial Intelligence, Natural Language Processing, or related field
- Research and/or work experience in machine learning, deep learning, and speech technology
- Experience with training deep neural networks for key speech tasks such as speech recognition, speech translation, speech synthesis, speaker diarization, sentiment analysis, acoustic event recognition, wake word, scene understanding, etc
- Experience in Python
- Experience in deep learning frameworks (PyTorch, Tensorflow, etc)
- Must obtain work authorization in country of employment at the time of hire, and maintain ongoing work authorization during employment
- Proven track record of achieving results as demonstrated by grants, fellowships, patents, as well as first-authored publications at workshops or conferences such as Interspeech, ACL, ICASSP or similar
- Experience working on speech LLMs
- Experience manipulating and analyzing complex, high-volume, high-dimensionality data from varying sources
- Experience working and communicating cross functionally in a team environment
- Intent to return to a degree-program after the completion of the internship/co-op
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