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Research Scientist

Reposted One Month Ago
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In-Office
New York, NY, USA
Mid level
In-Office
New York, NY, USA
Mid level
Drive RL research end-to-end for coding agents: form hypotheses, design experiments, build training/eval/data pipelines, train graders for non-verifiable rewards, improve datapoint quality, and develop realtime RL solutions to scale model performance.
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Our mission is to automate coding. The first step in our journey is to build the best tool for professional programmers, using a combination of inventive research, design, and engineering. Our organization is very flat, and our team is small and talent dense. We particularly like people who are truth-seeking, passionate, and creative. We enjoy spirited debate, crazy ideas, and shipping code.

Research Scientist

SpaceXAI is building the future of coding. We train frontier coding agents and scale RL on real user data to make them increasingly effective.

About the role

We’re looking for Research Scientists who can drive effective RL or mid-training research in a small-team setting. You’ll own ambiguous, hard research problems end-to-end: forming hypotheses, designing experiments, building the training/eval/data needed to test them, and pushing results into the next model. You should expect significantly more scope and autonomy than in other research labs.

What you’ll do
  • Improve our understanding of RL, what it takes to handle longer horizon tasks, and train with less compute

  • Train graders to improve performance on coding tasks with non-verifiable reward

  • Improve the quality and difficulty of datapoints we use for training our models

  • Realtime RL for coding agents

You may be a fit if
  • You have a deep background in RL and strong machine learning fundamentals

  • You’re an excellent programmer and software engineer

  • You can handle ambiguous research tasks with little guidance

  • You care a lot about data quality, and can dive into the data when appropriate

  • You are truth seeking, aiming to learn more about the science than proving your ideas are correct.

#LI-DNI

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