2026 Summer AI/ML Engineer Intern

About Dex

The AI Coworker in Chrome

Tech

Existing approaches—like computer-use data and Model Context Protocols—still overlook a fundamental element: a deep understanding of how individuals actually use software. Every person navigates their workday with unique mental models and personal systems for interacting with platforms and staying organized. These invisible frameworks shape productivity and workflow in ways that generic data can’t capture. How can we systematically capture, structure, and teach these personal workflows to AI—enabling it to become a truly proactive, personalized extension of each user?

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*** 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.