AI Tutor, Organic & Polymer Chemistry Specialist (nmr/spectroscopy) (contract), Handshake AI

Handshake Handshake · Enterprise · Remote · AI Trainer

This role focuses on evaluating AI models in chemistry, specifically using expertise in organic chemistry, polymer chemistry, and spectroscopy (NMR) to design prompts, assess model outputs, and identify reasoning errors. The specialist will contribute to quality standards and provide feedback to the AI team.

What you'd actually do

  1. Create and evaluate complex chemistry prompts across organic chemistry, polymer chemistry, NMR spectroscopy, and molecular analytical characterization
  2. Apply adversarial prompting strategies to induce and document model reasoning errors
  3. Critically assess the accuracy, depth, and scientific validity of AI-generated responses
  4. Contribute to quality standards and provide calibrated feedback to the broader team

Skills

Required

  • PhD in Chemistry or a closely related field
  • Graduate-level expertise across multiple areas of Chemistry
  • Prior hands-on experience in AI data annotation or RLHF
  • Excellent written communication and analytical skills

Nice to have

  • Publications in peer-reviewed chemistry or physics journals
  • Experience with adversarial prompting, model evaluation, or AI red teaming
  • Teaching, tutoring, or curriculum development experience in physical chemistry or theoretical sciences
  • Experience with computational chemistry tools (e.g., Gaussian, ORCA, MATLAB)
  • Background in scientific annotation or technical quality assurance

What the JD emphasized

  • AI model evaluation projects
  • assess model outputs at an expert level
  • identify where models break down in scientific reasoning
  • evaluate complex chemistry prompts
  • adversarial prompting strategies
  • document model reasoning errors
  • Critically assess the accuracy, depth, and scientific validity
  • calibrated feedback

Other signals

  • AI model evaluation
  • scientific reasoning
  • adversarial prompting
  • model reasoning errors
  • accuracy, depth, and scientific validity