About Thirdlayer
Continual learning for enterprise AI. Backed by Y Combinator.
About the role
Join us in pushing the boundaries of what's possible with LLMs and browser-native AI. You'll work on cutting-edge problems in agent systems, context handling, and tool use, while collaborating directly with our research team to bring novel approaches to production.
What they're looking for
- Research or work experience with RL environments, LLMs, modern AI frameworks, and/or ML
- Experience with prompt engineering strategies
- Strong foundation in Python and TypeScript
More about this role
Join us in pushing the boundaries of what's possible with LLMs and browser-native AI. You'll work on cutting-edge problems in agent systems, context handling, and tool use, while collaborating directly with our research team to bring novel approaches to production.
- Browser agent and tool-calling multi-agent systems.
- Evaluation frameworks for memory, efficiency, and accuracy.
- Memory and personalization layer for workflows
- Research or work experience with RL environments, LLMs, modern AI frameworks, and/or ML.
- Experience with prompt engineering strategies.
- Strong foundation in Python and TypeScript.
- Designing and creating tool-calling environments to evaluate and benchmark agent systems
- Agentic systems that predict and execute users’ next steps in complex workflows.
- Mapping user paths on real world software to API functionality and action trajectories.
- A searchable, self-updating memory store for continuously learning agents.
- A system to interpret DOM snapshots, mouse click events, and keyboard inputs to select browser actions.
- A context composer that feeds relevant info into LLM prompts based on user interactions, page content, and memory.
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