AI Engineer, RL

How do you judge something non-verifiable, like design? To solve subjective domains, we have to solve how to grade the difference between slop and great without the need for humans in the loop. Types of problems you’d work on

Research different grading methods and rubrics

Design unique tasks that can capture elements of “taste” and design capabilities

Build agent harnesses and context layers

Work on scalable RL infra

Work with internal research teams on our training pipelines

Work with the top frontier labs on how to craft environments to improve frontier models

What matters to us

Experience in building evals, RL environments, ML or post-training. Strong backend experience as well.

You like ambiguous, hard, creative problems, and want to make subjective domains verifiable

You’re a team player and have startup DNA: you move fast, adapt, no such thing is ‘not in scope’, you like to take ownership of things. You’ll be given a lot of room to run.

Bonus points

Open source contributions or personal projects that show you build things because you're curious

Background at creative companies (Figma, Notion, Canva, Adobe, Runway, etc.) or companies with strong index building/crawling (e.g. Firecrawl, Brave, Luma, Pika) or data (Mercor, Surge, etc.)