Cua

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.

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 Founding Engineer, you’ll help turn research prototypes into production-ready infrastructure - powering everything from secure agent runtimes to cross-cloud container orchestration. We’re looking for someone who brings deep technical ability, strong product instincts, and an eagerness to operate across layers - from OS-level virtualization to developer-facing APIs. You’ll work closely with the founding team on infrastructure design, developer tools, and open-source community building. Your contributions will shape how autonomous agents interact with real computers at scale - across macOS, Windows and Linux - and how developers deploy and trust them in production environments. Cua is for builders who care about reproducibility, system safety, and the developer experience of working with AI. If that sounds like you, we’d love to talk. Responsibilities Design and scale infrastructure to run real AI agents on isolated macOS and Linux containers Build orchestration systems across cloud providers (AWS, GCP, etc.) for deploying ephemeral agent environments Create intuitive APIs and CLIs for developers to launch and control agents Contribute to the design of secure, reproducible agent runtimes using Docker, KVM, or similar technologies Work closely with early customers, open-source contributors, and the founding team to define roadmap and architecture Publish engineering updates, blog posts, and technical documentation to grow the ecosystem Participate in product discussions, contribute to internal research, and help drive long-term technical vision Qualifications Required: 2+ years building and maintaining production infrastructure systems Proficiency in one or more of: Python, Go, TypeScript, or Rust Experience with backend system design, containers, and cloud environments Strong interest in developer tools, AI infrastructure, or distributed systems Comfortable operating in a fast-moving, ambiguous, startup environment Preferred: Experience with Docker, KVM, or other OS-level virtualization Familiarity with multi-cloud deployment and networking (e.g., AWS, GCP, Azure) Performance optimization and debugging experience (e.g., PostgreSQL tuning, cluster orchestration) Experience working with AI agents, LLM-generated code, or Copilot-style tools Prior open-source contributions or community involvement Based in or willing to relocate to SF What We Offer Early-stage ownership - Join as a founding engineer with equity and high influence Real traction - 9k+ GitHub stars and growing community of developers Technical scope - From system internals to developer UX to open-source leadership Impact - Define how general AI agents run safely and scalably in production How to Apply Please include: Your GitHub or portfolio (required) A short note on the most interesting developer or infrastructure problem you’ve helped solve Bonus: try building something with Cua or contribute to our docs - we notice contributors The base salary range for this role in San Francisco is $100,000-$150,000 USD per year, depending on experience and skill level. This role also includes equity and other benefits. Cua AI, Inc. is committed to fair and transparent compensation. We encourage applicants from all backgrounds to apply, regardless of gender, age, gender identity, sexual orientation, ethnicity, or belief. Personal data will be handled in accordance with the GDPR (EU Regulation 2016/679) and other applicable data privacy laws.