Thinking Machines Lab, San Francisco
As a Research Product Manager at Thinking Machines, you’ll partner closely with researchers and engineers to shape the capabilities of our frontier models and the methods that let people make those models their own. You’ll connect research direction, experimental evidence, and real-world needs, helping the team decide which capabilities to pursue, what to learn next, and where to invest.
A central focus of this role is mid-training: the work between pre-training and post-training that shapes what a model knows, the capabilities it develops, and how effectively it can learn afterward. This includes data and synthetic data strategies, training recipes, context extension, and capabilities across coding, math, reasoning, and knowledge-intensive work. You’ll help connect these choices to downstream model quality, adaptability, and usefulness.
The most interesting questions often span training stages. Which capabilities should we build into the model’s foundation? What makes a model easier to specialize through further training? How do we tell whether an improvement transfers to unfamiliar tasks, survives later training, and matters to the people using the model? You’ll help turn these questions into focused research priorities and clear decisions.
This role is for someone who enjoys working deeply inside research, can move between technical details and the broader opportunity, and brings independent judgment to problems where the right goal or metric is still emerging. Success means helping the team build differentiated technology and turn scientific progress into useful capabilities.
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.
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Source: the Thinking Machines Lab Ashby job board. We last checked this job 8 h ago. We first saw it 7 days ago. A job on a job board does not always mean that the team interviews people now.
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