Thinking Machines Lab, San Francisco
Mid-training is a step between pre-training and post-training, where we take a base model and train it into the foundation for reasoning. This role owns the late-stage training responsibility that shape what our models are fundamentally capable of, including things like synthetic data strategies, the data mix, quality uplift, context extension and capabilities across coding, math, reasoning, and so on.
This role blends fundamental research and practical engineering, as we do not distinguish between the two internally. It's an excellent fit for someone comfortable working across the boundary of pre-training and post-training, and who wants to shape what our models can do at their core.
Preferred qualifications (we encourage you to apply if you meet some but not all of these):
The mission of Thinking Machines is to build AI that extends human will and judgment. We are training frontier models with Inkling, developing Tinker to let people make models their own, and crafting interfaces that broaden human-AI communication. We believe the future worth building is human, and we're hiring people who want to build it.
As set forth in Thinking Machines' Equal Employment Opportunity policy, we do not discriminate on the basis of any protected group status under any applicable law.
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