Source description
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 You'll Build
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Browser agent and tool-calling systems.
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Evaluation frameworks for agent performance.
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Memory and personalization layer for workflows
Requirements
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Research/work experience with 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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Agentic systems that predict and execute users’ next steps in complex workflows.
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A searchable, self-updating memory store for personalized browser agent behaviour.
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Designing intuitive interfaces for how users should delegate and override AI actions.
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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