Remote Chemistry AI Data Trainer — Masters Level

Alignerr Corp.; Manchester; Remote; GBP 34,000 - 69,000; Part time

Benefits offered by this job

Fully remote work

Flexible hours

Freelance autonomy

Job summary

Alignerr is seeking a Chemistry Masters – AI Data Trainer to design and vet chemistry problems for next-gen AI models. This fully remote, hourly-contract role focuses on developing rigorous problem sets and solutions across undergraduate to Masters-level topics, with flexible scheduling.

Ideal candidates hold a Master’s in Chemistry or related field, possess strong analytical and written communication skills, and can work independently with minimal supervision.

Qualifications

• Master's degree in Chemistry or a related field.
• Strong analytical and problem-solving skills.
• Clear written communication.
• Detail-oriented with rigorous reasoning.
• Self-motivated and able to work independently.
• No prior AI experience required.

Responsibilities

• Design advanced chemistry problems to test AI performance across domains.
• Develop clear, step-by-step solutions with precise reasoning.
• Evaluate AI outputs for scientific accuracy and depth of reasoning.
• Collaborate with researchers to refine benchmarks from undergraduate to Masters level.
• Provide structured written feedback to improve AI model performance.

Skills

Analytical thinking

Written communication

Detail-oriented

Independent work

Asynchronous work

Education

Master's degree in Chemistry or related field

Tools

Data annotation experience

Familiarity with AI research workflows

Job description

Alignerr is seeking a Chemistry Masters – AI Data Trainer to design and vet chemistry problems for next-gen AI models. This fully remote, hourly-contract role focuses on developing rigorous problem sets and solutions across undergraduate to Masters-level topics, with flexible scheduling.

Ideal candidates hold a Master’s in Chemistry or related field, possess strong analytical and written communication skills, and can work independently with minimal supervision.