Source description
About the role
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
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Browser agent and tool-calling multi-agent systems.
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Evaluation frameworks for memory, efficiency, and accuracy.
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Memory and personalization layer for workflows
Requirements
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Research or work experience with RL environments, LLMs, modern AI frameworks, and/or ML.
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Experience with prompt engineering strategies.
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Strong foundation in Python and TypeScript.
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Sample Projects
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Designing and creating tool-calling environments to evaluate and benchmark agent systems
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Agentic systems that predict and execute users’ next steps in complex workflows.
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Mapping user paths on real world software to API functionality and action trajectories.
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A searchable, self-updating memory store for continuously learning agents.
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A system to interpret DOM snapshots, mouse click events, and keyboard inputs to select browser actions.
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A context composer that feeds relevant info into LLM prompts based on user interactions, page content, and memory.
More at Dex