Jay Chooi

CEO and Co-Founder, Robocurve

  • I am building Robocurve, a YC-backed Public Benefit Corporation developing open-source tools and independent benchmarks to measure how well AI and robots can do real-world tasks. Previously, I was a Research Fellow at MATS, where I worked on technical AI safety research with Professor Shi Feng. Before that, I spent time at AWS and at UK AISI.

    I recently graduated from Harvard with a Bachelor's in Computer Science and Mathematics, with a concurrent Master's in Statistics. My thesis, Computational Perspectives on Democracy in the Age of AI, was awarded Highest Honors. I was elected a Rhodes Scholar in 2025. In 2024, I correctly forecasted the US Presidential Election results in all 50 states. I am a gold medalist at the 2021 International Olympiad in Astronomy and Astrophysics.

    I work on preparing society for powerful artificial intelligence. My research interests are forecasting physical automation and understanding how, or if, society can flourish and remain stable when human labor is no longer the main source of political power and economic leverage.

  • - Designing robotics benchmarks.
    - Running evaluations of frontier AI models.
    - Working with actual robots (e.g. bimanual arms, humanoids, quadrupeds).
    - Developing our open-source evaluation harness used both internally and externally.
    - Engineering the low-latency inference infrastructure for robotics foundation models.
    - Measuring recursive self-improvement of AI in robotics capabilities.
    - Architecting our research roadmap on prioritizing task families, model families and embodiments.
    - Scaling to hundreds of parallel real-world robotics evals by year end.

  • Requirements:
    - Exceptional software engineering skills with agentic tools (e.g. Claude Code, Codex)
    - Exceptional communication skills
    - Willingness to learn and move fast
    - (After CBAI) Openness to convert to a full time Member of Technical Staff
    - (After CBAI) Openness to work in-person at our office in San Francisco

    Great to have but not required:
    - Experience in AI evaluations (e.g. Inspect AI)
    - Experience in robotics (e.g. Master's/PhD/robotics lab experience)
    - Context on AI safety and the future trajectory of AI (e.g. BlueDot fellowship, SPAR, Astra, MATS)

    Aside from technical skills, we find that strong candidates have these personal qualities:
    - Reasoning transparency. Arriving at conclusions through verbalized/written reasoning instead of relying on unjustifiable hunches.
    - Overcommunication over undercommunication.
    - Prioritizing what is important. Research directions follow a power law on their impact.
    - Gives honest feedback to teammates and implements honest feedback from teammates.
    - Strong team player.