Research Intern (Summer 2026)

Overview

Cua is building the infrastructure that enables general-purpose AI agents to safely and scalably use real computers and applications.

We're a small team backed by Y Combinator and top-tier investors, and our open-source tools are already used by thousands of developers. As a Research Intern , you’ll help prototype, test, and benchmark multi-modal LLM-based agents - from data pipelines to orchestration systems.

You’ll collaborate with engineers and researchers to turn cutting-edge ideas into real systems and benchmarks that can be shared with the community. This is a chance to contribute to open-source research, design experiments, and explore the frontiers of agentic AI.

Responsibilities

• Generate and curate large-scale, high-quality multi-modal data (GUIs, browsers, system UIs)

• Design and test single- and multi-agent systems for data and computer use

• Automate benchmarking of agent orchestration (with or without human-in-the-loop)

• Explore new training and inference techniques to boost reasoning and action-taking (e.g., RL-based agents)

• Develop benchmarks, tools, and datasets to evaluate agentic capabilities on Cua

• Collaborate with the founding team and contribute to research publications, open-source tools, and the broader community

Qualifications

• Required:

• Currently a PhD student in Computer Science or related field (strong Master’s considered)

• Experience in applied research with a solid publication record

• Familiarity with modern multi-modal or reasoning agents (e.g., OS-Atlas, Qwen, GUI-R1)

• Hands-on experience with PyTorch , Python , and cloud compute (AWS, GCP, etc.)

• Comfortable designing experiments, evaluating models, and working with multi-modal data

• Excited by generative AI, agent systems, and pushing the boundaries of what’s possible

• Preferred:

• Experience with reinforcement learning or agent-based training methods

• Prior contributions to open-source projects or benchmark design

• Familiarity with large-scale dataset construction and evaluation pipelines

• Interest in bridging research and engineering for real-world applications

• Based in or able to spend time in SF/Bay Area (preferred), but remote OK

What We Offer

• Research impact – Opportunity to publish, open-source, and influence open agent research

• Hands-on projects – Work directly with engineers and researchers on cutting-edge systems

• Open-source visibility – Contribute benchmarks and datasets used by the community

• Flexible setup – Remote-friendly; SF-based team

• Learning environment – Collaborate on projects at the intersection of infrastructure and AI research

• How to Apply

• Please include:

• Your CV and GitHub/portfolio

• A short note on a research problem you’d like to tackle

• Bonus: try building something with Cua or suggest a benchmark idea — we notice contributors

• This is a paid internship (3-month full-time preferred; part-time considered). Compensation will depend on location and experience.

• Cua AI, Inc. is committed to fair and transparent opportunities. We encourage applicants from all backgrounds, identities, and walks of life to apply.

• Personal data will be handled in accordance with the GDPR (EU Regulation 2016/679) and other applicable data privacy laws.