Guide Labs
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About
Guide Labs is building interpretable AI systems and foundation models that prioritize human understanding, trust, and debugging. Their research focuses on creating reliable explanations and justifications, addressing issues with current AI systems that produce unreliable or unrelated explanations. They've developed methods for training models that produce human-understandable factors for outputs, reliable context citations, and specification of training data influence. Their team has extensive experience in interpretable machine learning, with publications at top ML conferences and development of the first interpretable generative diffusion model and LLM. They are hiring for several roles in San Francisco, including Research Interns, Full-stack Developers, Research Scientists, and Machine Learning Engineers.
Platform
Task
Features
• human-understandable explanations
• interpretable ai systems
• foundation models
• context citations
• trustworthy outputs
• reliable debugging
• training data influence specification
Job Opportunities
Research Intern
Guide Labs develops interpretable and auditable AI systems and foundation models for reliable debugging, trust, and human understanding.
Education Requirements:
PhD preferred
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Research Scientist
Guide Labs develops interpretable and auditable AI systems and foundation models for reliable debugging, trust, and human understanding.
Education Requirements:
PhD preferred
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Machine Learning Engineer
Guide Labs develops interpretable and auditable AI systems and foundation models for reliable debugging, trust, and human understanding.
Education Requirements:
PhD preferred
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