Research Scientist Intern, Audio AI (PhD)

Meta•Menlo Park, CA

1d•$7,650 - $12,667

About The Position

Meta is seeking Research Scientist Interns to join the Media Foundation Core Audio team, which develops audio technologies used across WhatsApp, Messenger, Instagram, Facebook, and Meta AI experiences. The work spans real-time calling, conversational AI, voice and media messaging, Live, and video-on-demand. Each intern will work on a focused research problem at the intersection of machine learning, audio and speech signal processing, human perception, and efficient systems. Potential topics include streaming speech and audio enhancement; restoration and super-resolution; neural audio codecs and compression; perceptual and context-aware quality metrics; multimodal evaluation; and efficient on-device or server inference. Projects will be selected based on the intern’s expertise and team priorities. The work combines research depth with practical constraints such as latency, bitrate, compute, memory, power, robustness, and safe fallback. Interns collaborate with research scientists, software engineers, and product partners to define problems, develop and evaluate solutions, and identify paths from research results to product impact. Internships last 12 to 16 weeks, or 24 weeks, with various start dates throughout the year.

Requirements

Currently has or is in the process of obtaining a Ph.D. in Computer Science, Artificial Intelligence, Natural Language Processing, Speech Recognition, Sentiment Analysis, Computer Vision, or a relevant technical field.
Must obtain work authorization in the country of employment by the time of hire and maintain ongoing work authorization during employment.
Experience with Python, C++, C, Java, or another related language.
Experience with deep learning frameworks such as PyTorch or TensorFlow.
Familiarity with machine learning and common deep learning architectures.

Nice To Haves

Intent to return to the degree program after completing the internship or co-op.
Research achievements demonstrated through grants, fellowships, patents, or publications at leading AI conferences such as NeurIPS, ICML, ICLR, ACL, EMNLP, or KDD.
Prior research or project experience in one or more of reinforcement learning, pre-training and supervised fine-tuning of large language models, sequence modeling, diffusion models, and their applications in recommendation systems.
Software development experience through technical internships, work experience, coding competitions, or widely used contributions to open-source machine-learning repositories.
Experience working and communicating cross-functionally in a fast-paced team environment, with the ability to identify research opportunities in real-world applications, choose appropriate machine-learning methods, and proactively drive iterations through clear analysis of results.

Responsibilities

Perform research to advance audio, speech, multimodal, and machine learning technologies.
Design, train, and evaluate models for audio applications such as enhancement, restoration, compression, generation, or quality understanding.
Build reproducible evaluation pipelines using objective metrics, human listening tests, robustness analysis, and system-level measurements.
Analyze and improve model quality, efficiency, latency, scalability, and stability under practical device, network, and serving constraints.
Collaborate with researchers, software engineers, and cross-functional partners; communicate research plans, progress, tradeoffs, and results.
Publish research results and contribute to research that can be applied to Meta product development.