Meta
Research Scientist Intern, Feed Recommendations (PhD)
Bellevue, WA · Internship · Posted Oct 22, 2026
- Experience
- No number of years specified. Internship duration: 12 to 16 weeks, or 24 weeks.
- Education
- 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.
- Visa sponsorship
- Must obtain work authorization in the country of employment at the time of hire and maintain ongoing work authorization during employment.
About the job
Research and develop machine-learning methods for Facebook Feed recommendations, including generating relevant content sequences and improving deployed systems.
What you'll do
- Develop novel NLP algorithms and systems using deep learning and machine learning on large data resources.
- Analyze and improve the efficiency, scalability, and stability of deployed systems.
- Collaborate on research, communicate findings, and publish work relevant to Meta products.
What they ask for
- Currently has or is pursuing a Ph.D. in a listed or relevant technical field.
- Experience with a programming language such as Python, C++, C, or Java, and with PyTorch or TensorFlow.
- Experience building systems using machine learning, deep learning, or NLP; familiarity with generative-model training and architectures such as Transformers, GPTs, or BERT.
- Must obtain and maintain work authorization in the country of employment; intends to return to the degree program after the internship.
Nice to have
- Research or project experience in reinforcement learning, language-model training and fine-tuning, sequence modeling, diffusion models, or recommendation applications.
- Research achievements such as publications at leading AI conferences, and software-development experience demonstrated through internships, competitions, or open-source contributions.
Pay
$7,650/month to $12,667/month (base salary)
Tools
Python, C++, C, Java, Pytorch, Tensorflow, Transformers, GPTs, BERT
AI focus
Develop NLP and generative recommendation methods to generate relevant content sequences for users, drawing on deep learning, machine learning, and large-scale data.
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