Job Title: Chemistry Researcher - AI Trainer

Job Type: Part-time

Location: Remote

Job Summary:

Join our customer's team as a Chemistry Researcher - AI Trainer and help shape the future of artificial intelligence. Leverage your deep expertise to craft, refine, and evaluate high-quality training data for AI models. Work remotely with world-class machine learning experts, directly influencing how AI understands and communicates advanced chemistry concepts.

Key Responsibilities:

• Create, annotate, and evaluate specialized chemistry training datasets in various formats, including text, diagrams, and video.
• Act as a subject-matter expert in Chemical Bonding and Molecular Structure, Reaction Mechanisms and Kinetics, and Spectroscopy and Analytical Techniques to support robust AI model development.
• Author clear, pedagogically sound explanations and solutions for complex chemistry problems using diverse instructional approaches.
• Audit and improve AI-generated chemistry content, ensuring scientific accuracy and linguistic precision.
• Perform rigorous quality control reviews of materials produced by other experts for consistency and accuracy.
• Collaborate with machine learning scientists and engineers to refine data annotation guidelines, resolve edge cases, and optimize workflows.

Required Skills and Qualifications:

• PhD in Chemistry or closely related field.
• Exceptional English language proficiency (CEFR C2 or equivalent), with excellent written and verbal communication skills.
• Strong familiarity with U.S. academic standards and scientific conventions.
• Outstanding analytical and problem-solving skills within data-rich environments.
• Keen attention to detail and the ability to interpret and improve detailed annotation protocols.
• Self-motivated with proven ability to exercise sound judgment in dynamic or ambiguous scenarios.

Preferred Qualifications:

• Experience with AI/ML workflows, prompt engineering, or large language model training and evaluation.
• Background in data annotation, instructional design, or content evaluation for technology-driven educational platforms.