# **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.
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