Job description

The Meta Reality Labs Research team brings together researchers, developers, and engineers to build the future of augmented and virtual reality. Our research spans the technologies that enable next-generation AR glasses and VR headsets, with the goal of transforming how people interact with their surroundings and connect with one another. The Reality Labs Research audio team develops technologies that redefine human hearing and communication. We seek to help people understand the world around them, communicate in challenging listening environments, and connect across languages. Learn more about our research here. We are seeking Research Scientist Interns to advance multimodal large language models (MLLMs) and speech-to-speech translation (S2ST) for next-generation wearable and AR/VR experiences. Research opportunities include models that integrate audio, speech, vision, and language for multimodal understanding and reasoning; conversational speech models; and streaming speech translation that preserves meaning, speaker characteristics, and expressive prosody. Interns will investigate research questions in one or more of these areas, develop and evaluate novel models, and collaborate with researchers and engineers to demonstrate their potential in real-world applications. Our internships are twelve (12) to twenty-four (24) weeks long, with various start dates throughout the year. Conduct original research in multimodal large language models, speech foundation models, or speech-to-speech translation. Develop models that jointly understand and reason over audio, speech, visual, and textual inputs, or generate natural speech across languages. Investigate methods for model pretraining, multimodal alignment, instruction tuning, or streaming inference. Design and execute experiments, establish baselines, and evaluate model quality, robustness, latency, and computational efficiency. Collaborate with researchers and engineers across speech, audio, computer vision, and language modeling. Communicate research ideas, progress, and results through presentations, technical reports, and research publications. Currently has, or is in the process of obtaining, a PhD degree in Computer Science, Artificial Intelligence, Machine Learning, Electrical Engineering, Signal Processing, Computational Linguistics, or a related STEM field 3+ years of experience programming in Python or a similar language 3+ years of experience with machine learning frameworks such as PyTorch or TensorFlow 2+ years of experience developing computational models in one or more of the following areas: speech processing, natural language processing, multimodal learning, or audio-visual learning Must obtain work authorization in the country of employment at the time of hire and maintain ongoing work authorization during employment Research experience in one or more of the following: Multimodal large language models, including audio-language or audio-visual-language understanding, alignment, and reasoning. Speech-to-speech translation, simultaneous translation, multilingual speech modeling, or streaming speech generation. Speech foundation models, neural audio codecs, speech tokenization, or expressive speech synthesis Experience pretraining or fine-tuning large models using distributed training and large-scale datasets Experience evaluating multimodal reasoning or speech translation, including translation accuracy, speech naturalness, speaker similarity, and streaming latency Demonstrated research contributions through publications at venues such as NeurIPS, ICML, ICLR, ACL, EMNLP, CVPR, ICCV, ECCV, ICASSP, or Interspeech Demonstrated software engineering experience through internships, research projects, or contributions to open-source repositories Experience collaborating and communicating across disciplines Intent to return to a degree program after completing the internship/co-op

Requirements

Must-haves

Interns will investigate research questions in one or more of these areas, develop and evaluate novel models, and collaborate with researchers and engineers to demonstrate their potential in real-world applications.
Our internships are twelve (12) to twenty-four (24) weeks long, with various start dates throughout the year.

Nice-to-haves

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Keywords to mirror

machine learningpython

Platform: meta
Effort: medium

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