Dex Verified
Software, Productivity Tools, Personal CRM
2026 Summer AI/ML Engineer Intern
San Francisco, California, United StatesOnsiteInternshipJunior / Entry-level$6,000–$10,000 /yrPosted 2 months agoHidden Gem · YC Startup
Role summary
This internship focuses on developing browser-native AI and Large Language Models (LLMs) for agent systems, context handling, and tool use. Interns will collaborate with a research team to build browser agents, multi-agent systems, evaluation frameworks for memory and accuracy, and a memory/personalization layer. Key requirements include experience with RL environments, LLMs, AI frameworks, ML, prompt engineering, Python, and TypeScript.
# **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.
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.