As the leading data and evaluation partner for frontier AI companies, Scale plays an integral role in understanding the capabilities and safeguarding large language models (LLMs). Safety, Evaluations and Alignment Lab (SEAL) is Scale’s frontier research effort dedicated to tackling the challenging research problems in evaluation, red teaming, and alignment of advanced AI systems.
We are actively seeking talented researchers to join us in shaping the landscape for safety and transparency for the entire AI industry. We support collaborations across the industry and academia and the publication of our research findings.

As a Research Scientist working on Scalable Oversight, you will develop and evaluate methods for evaluation and supervision of advanced AI systems. For example, you might do any or all of the following:

• Design experiments to exemplify failure modes of current supervision protocols for language models
• Design experiments to simulate expertise and capability gaps between supervisor and model for scalable oversight experiments
• Develop new supervision protocols and gather human annotations using these protocols
• Train language models using reinforcement learning, analyzing their behavior and comparing between models

ABOUT US:

At Scale, we believe that the transition from traditional software to AI is one of the most important shifts of our time. Our mission is to make that happen faster across every industry, and our team is transforming how organizations build and deploy AI. Our products power the world’s most advanced LLMs, generative models, and computer vision models. We are trusted by generative AI companies such as OpenAI, Meta, and Microsoft, government agencies like the U.S. Army and U.S. Air Force, and enterprises including GM and Accenture. We are expanding our team to accelerate the development of AI applications.
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• Design experiments to exemplify failure modes of current supervision protocols for language models
• Design experiments to simulate expertise and capability gaps between supervisor and model for scalable oversight experiments
• Develop new supervision protocols and gather human annotations using these protocols
• Train language models using reinforcement learning, analyzing their behavior and comparing between model