2026 Summer Research Engineer Intern

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 You'll Build

• Browser agent and tool-calling multi-agent systems.
• Evaluation frameworks for memory, efficiency, and accuracy.
• Memory and personalization layer for workflows

Requirements

• 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.

Sample Projects

• 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.