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.