Role focuses on evaluating AI models in chemistry, designing prompts, assessing outputs, and identifying reasoning errors. Requires PhD in Chemistry and experience in AI data annotation or RLHF.

The role focuses on evaluating and stress-testing complex scientific prompts for large language models, specifically in biology. The specialist will design high-difficulty prompts, identify reasoning errors and weaknesses in model outputs, and apply adversarial prompting techniques. This is a research-oriented role focused on improving AI model capabilities through expert evaluation.

This role focuses on evaluating AI models, specifically in physics, by crafting and assessing challenging problems, probing model reasoning, and identifying failures using adversarial prompting. It involves providing expert critique of AI responses and ensuring quality benchmarks are met. Prior experience in AI data annotation or RLHF is required, with a PhD in Physics or a related field.

Machine Learning PhDs needed for hourly contract work to evaluate AI-generated content and provide feedback on machine learning reasoning, proof construction, and technical problem-solving. This role focuses on assessing AI responses for accuracy, rigor, and relevance to real-world physics research.

This role involves evaluating AI-generated responses related to Ngspice and analog circuit design, providing feedback to improve AI understanding. It requires expertise in Ngspice and circuit simulation but no prior AI experience.

Seeking Math PhDs to evaluate AI-generated content and provide feedback on mathematical reasoning, proof construction, and technical problem-solving. This is a flexible, hourly contract role with no prior AI experience required.