At Guide Labs, we are building AI systems that are engineered, from the start, to be modular, easily audited, steered, and understood by humans. Conventional model development approaches optimize for narrow performance measures, and jettison key interpretability (and reliability) concerns until after the model has been pre-trained. This approach is fundamentally broken. Guide Labs reimagines the entire model development process: the training dataset, model’s architecture, loss function, pre-training and post-training algorithm, all the way to user interaction with the model.
Team
We are interpretability researchers and engineers that have been responsible for major advances in the field. We have set out to rethink the way machine learning models, AI agents, and systems broadly are developed.
A note about experience
We do not care about formal credentials. If you share our vision, have evidence that demonstrates that you can be effective in this role, and would like to get involved, please reach out. If some of the above doesn’t line up perfectly with your profile or past experience, we still encourage you to apply!
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Job details are sourced from the employer's original posting.
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Guide Labs builds interpretable AI systems that make machine learning models more transparent and explainable.