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Letta

Memory-enabled platform for stateful AI agents

Research Engineer / Scientist - Self-Improvement

AI ResearchConfirmed live in the last 24 hours
Full-timeSan Francisco, CA, USANo salary listed

About the Job

Requirements

  • Expertise in machine learning, particularly large language models and continual learning.
  • Familiarity with agent frameworks and prompt optimization.
  • A track record of impactful research through breakthrough publications and/or open-source contributions.
  • Ability to balance execution speed with empirical rigor.
  • Real-world impact beyond pure academic work.

Responsibilities

  • Develop prompt optimization and system prompt learning methods that allow agents to continuously learn from long-horizon tasks.
  • Develop methods that allow agents to automatically generate and test hypotheses in an environment or seek out and improve their own weaknesses.
  • Improve the efficiency of learning from long-running agentic tasks.
  • Design and run experiments to measure self-improvement scalably.
  • Advance the field through open publishing of research through papers, technical reports, blog posts, and open-source code.

About the Company

Letta

Memory-enabled platform for stateful AI agents

Letta provides a memory management platform for building and deploying stateful AI agents. It offers a hosted, model-agnostic API service called Letta Cloud and an Agent Development Environment (ADE) with a REST API and SDKs to build, run, and test agents locally. The platform lets developers create AI agents that maintain context and learn from long-running conversations by managing memory and context over time, enabling continued learning from user interactions. Letta’s technology draws on UC Berkeley research and MemGPT for memory management, positioning it to help applications that require long-term reasoning and evolving agents. Letta differentiates itself through its focus on memory-enabled, stateful agents, a fully hosted API with scalable cloud deployment, and developer tools for end-to-end agent development. The company’s goal is to help developers and businesses build AI agents that can reason, remember, and improve across extended conversations at scale.

Company size
11-50
Company stage
Seed
Total funding
$10M
Headquarters
San Francisco, CA
Founded
2024

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