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Research Scientist Intern, FAIR – Multi-Agent Systems and Memory (PhD)
Bellevue, WA +2 · Internship · Posted Oct 21, 2026
- Location
- Bellevue, WA
Seattle, WA
New York, NY - Education
- Currently has or is in the process of obtaining a PhD degree in Computer Science, Machine Learning, Artificial Intelligence, Natural Language Processing, or a related 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
Conduct fundamental research on AI agent memory and multi-agent collaboration, developing and evaluating algorithms that help agents retain context, share knowledge, and adapt on complex tasks.
What you'll do
- Develop algorithms and prototypes for agent memory, inter-agent coordination, or adaptive workflows; run experiments against strong baselines.
- Analyze agent performance, trajectories, failure modes, computational cost, and generalization.
- Review research, formulate research questions, and prepare and present reports or publications.
What they ask for
- Currently has or is pursuing a PhD in Computer Science, Machine Learning, Artificial Intelligence, Natural Language Processing, or a related field.
- Research or work experience in large language models, machine learning, deep learning, reinforcement learning, or related areas.
- Experience with Python, C++, or related languages; experience building and evaluating language-model agents and implementing research prototypes.
- Must obtain and maintain work authorization in the country of employment; intend to return to the degree program after the internship.
Nice to have
- Track record of significant research results, such as publications at leading AI conferences, grants, or patents.
- Research experience in agent memory, context compression, multi-agent systems, agent orchestration, self-improvement, or automated scientific research.
Pay
$7,650/month to $12,667/month (base salary)
Tools
Python, C++, PyTorch
AI focus
Fundamental research on agent memory, multi-agent collaboration, long-context modeling, self-improving agents, and automated scientific research.
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