Cua is building the infrastructure that lets general AI agents safely and scalably use Computers and Apps like humans do.
With 9k+ GitHub stars in just 4 months and a seed round closed, we’re providing:
Cua is building infrastructure for safely and scalably running general AI agents on real computers and apps.
With 9k+ GitHub stars in just 4 months and backing from Y Combinator, we’re pushing the frontier of agentic AI.
We’re looking for a Research Intern to help prototype, test, and benchmark multi-modal LLM-based agents—from data pipelines to orchestration systems.
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WHAT YOU’LL DO
Collaborate with engineers and researchers to turn cutting-edge ideas into systems and benchmarks used by the community.
Example projects:
• Generate and curate large-scale, high-quality multi-modal data (GUIs, browser, system UIs)
• Design and test single/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
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WHAT WE’RE LOOKING FOR
• PhD student in CS 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 with PyTorch, Python, cloud compute (AWS/GCP)
• Comfortable designing experiments, evaluating models, and working with multi-modal data
• Excited by generative AI, agent systems, and pushing what’s possible
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LOGISTICS
• 3-month full-time preferred; part-time considered
• Remote-friendly; SF-based team
• Opportunity to publish, open-source, and influence open agent research
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APPLY
• CV and GitHub/portfolio
• Short note on a research problem you’d like to tackle
We welcome applicants from all backgrounds, identities, and walks of life.
We're looking for different roles to help us push this vision forward - turning cutting-edge research prototypes into real, deployable systems.
If you’re obsessed with developer tools, infrastructure, and making AI agents go from toy demos to robust, real-world tools - we want to talk.
internSan Francisco, CA, US / Remote (US)Machine learning$96K - $110KAny
fulltimeSan Francisco, CA, US / Remote (US)Machine learning$100K - $130K0.25% - 0.75%Any (new grads ok)
fulltimeSan Francisco, CA, USFull stack$100K - $150K0.50% - 0.75%1+ years
fulltimeMadrid, MD, ES / Madrid, Community of Madrid, ES / Remote (ES)Full stack$40K - $70K0.25% - 0.50%1+ years