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Catalog

Founding Engineer

Posted 5 Days Ago
In-Office
San Francisco, CA, USA
Entry level
In-Office
San Francisco, CA, USA
Entry level
Founding Engineer will work across AI research and engineering to develop reinforcement learning and post-training systems. Responsibilities include exploring open-ended problems, building model-learning systems, moving prototypes into production, shaping technical direction, and helping establish engineering culture. The role requires strong engineering judgment, independent problem-solving, rapid execution, and enthusiasm for intelligence and model capabilities. Experience with AI agents, machine learning, reinforcement learning, post-training, early products, research tools, or technical infrastructure is preferred.
The summary above was generated by AI

Catalog is building environments that help push frontier intelligence forward. We work on how AI systems learn from experience and become capable of increasingly complex, useful work.

Our focus is reinforcement learning and post-training. Better environments and feedback can unlock new capabilities, and we want to help define what the next generation of AI can do. The work is early, the questions are open, and there is room to make a lasting contribution.

Role

As a Founding Engineer, you’ll work across research and engineering to turn ambitious ideas into working systems. You’ll help decide which problems matter, explore new approaches, and build the foundations of Catalog.

You’ll have meaningful ownership over the technical direction, product, and engineering culture, working closely with the founders from the earliest stages.

What you’ll do
  • Take on open-ended problems at the intersection of AI research and engineering.

  • Build systems that help models learn, improve, and perform more reliably.

  • Move between experiments, prototypes, and production as the work evolves.

  • Help shape our technical approach and the team we build around it.

You might be a fit if you
  • Have strong engineering instincts and a track record of building things that work.

  • Are deeply curious about intelligence, how models learn, and what they could become capable of.

  • Enjoy ambiguous problems and can turn an idea into something concrete.

  • Move quickly, think independently, and care about the quality of your work.

  • Want high ownership in a small, ambitious team in San Francisco.

Nice to have
  • Experience with AI agents, machine learning, reinforcement learning, or post-training.

  • Built early products, research tools, or technical infrastructure.

  • Research, open-source contributions, or independent projects that show how you think.

How we work

Small team, high trust, high intensity. We bias to in-person collaboration in North Beach, San Francisco. We debate, decide, and ship.

If there appears to be a fit, we'll reach out to schedule 2-3 short technicals. After, we'll schedule an onsite in our office, where you'll work on a small project, discuss ideas, and meet the team.

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