Research Scientist Intern - Multi-Agent Systems and Memory

Meta; Bellevue (WA); On-site; USD 28,000 - 41,000; Full time

Job summary

Meta is seeking Research Interns to advance Fundamental AI Research (FAIR) Communication & Language teams focused on multi-agent systems and memory. Interns will explore how agents retain knowledge across extended interactions, share information effectively, and adapt workflows through experience.

The program spans 12 to 24 weeks with flexible start dates. Ideal candidates have expertise in multi-agent collaboration, memory representations, long-context modeling, self-improving agents,

Qualifications

• Candidates with expertise in multi-agent systems, coordination and communication.
• Expertise in agentic memory, long-term memory and memory retrieval.
• Experience with long-context modeling and KV-cache compression.
• Interest in self-improving agents, test-time learning and adaptation.
• Knowledge of reinforcement learning and automated scientific research.

Responsibilities

• Investigate how AI agents retain and use knowledge across extended interactions.
• Develop compact memory representations and improve inter-agent communication.
• Explore automatic optimization of agent workflows and harnesses.

Skills

Multi-agent systems

Agentic memory

Long-context modeling

Self-improving agents

Reasoning and tool use

Job description

Meta is seeking Research Interns to join our Fundamental AI Research (FAIR) Communication & Language teams working on multi-agent systems and memory. These teams are committed to advancing artificial intelligence through fundamental breakthroughs that enable agents to reason, learn from experience, and collaborate on complex tasks. We are looking for individuals passionate about large language models, agentic systems, machine learning, and reinforcement learning. Our interns have the opportunity to make core algorithmic advances and evaluate their ideas at scale.

This internship will investigate how AI agents can retain and use knowledge across extended interactions, share information effectively, and adapt their workflows based on experience. Our research connects memory and multi-agent collaboration with self-improving systems for automated scientific research. Potential directions include developing compact memory representations, improving inter-agent communication and coordination, and automatically optimizing agent harnesses. The specific research question will be shaped by the intern's interests and early experimental findings.

We are especially interested in candidates with expertise in one or more of the following areas:

• Multi-agent systems, collaboration, coordination, communication, and shared knowledge
• Agentic memory, long-term memory, implicit or parametric memory, and memory retrieval and utilization
• Long-context modeling, context compression and compaction, and KV-cache compression
• Self-improving agents, adaptive agent workflows, agent harness optimization, and test-time learning and adaptation
• Reasoning, planning, tool use, reinforcement learning, and automated scientific research

Our team at Meta AI offers twelve (12) to twenty-four (24) weeks long internships and we have various start dates throughout the year. To learn more about our research, visit https://ai.meta.com/research/.