Meta
Research Scientist Intern, Audio AI (PhD)
Bellevue, WA +1 · Internship · Posted Oct 26, 2026
- Location
- Bellevue, WA
Menlo Park, CA - Education
- Ph.D. in Computer Science, Artificial Intelligence, Natural Language Processing, Speech Recognition, Sentiment Analysis, Computer Vision, or relevant technical field.
- Visa sponsorship
- Must obtain work authorization in country of employment at the time of hire and maintain ongoing work authorization during employment.
About the job
Conduct focused research in audio and speech machine learning, developing and evaluating models and efficient systems for Meta’s communication and media products.
What you'll do
- Research and develop models for audio applications such as enhancement, restoration, compression, generation, or quality understanding.
- Build reproducible evaluations and improve quality, efficiency, latency, scalability, and stability under practical constraints.
- Collaborate across research and product teams, communicate findings, and publish results that may support Meta products.
What they ask for
- Currently pursuing or obtaining a Ph.D. in a listed or relevant technical field.
- Must obtain and maintain work authorization in the country of employment.
- Experience with a programming language and deep learning frameworks such as Pytorch or Tensorflow; familiarity with machine learning and common deep learning architectures.
- Intent to return to the degree program after the internship; proven research achievements and relevant research or project experience.
Nice to have
- Demonstrated software development experience through internships, work, competitions, or open-source contributions.
- Experience communicating cross-functionally and identifying research opportunities in real-world applications.
Pay
$7,650/month to $12,667/month (USD; base salary)
Tools
Python, C++, C, Java, Pytorch, Tensorflow
AI focus
Research and development in audio, speech, multimodal, and machine learning, including enhancement, restoration, compression, generation, quality evaluation, and efficient inference.
Model-written summary · the original posting is authoritative