Quant STEM Bachelor AI Training Reviewer (English)

OpenTrain AI, Inc.; United States; Remote; USD 28,000 - 62,000; Part time

Job summary

OpenTrain AI, Inc. seeks a Quant STEM Bachelor AI Training Reviewer (English) to review homework problems and AI responses across quantitative subjects. You will explain reasoning, identify errors, and provide detailed feedback on accuracy and educational value.

This remote, part-time contractor role pays $20 to $45 per hour and involves analyzing problems in mathematics, physics, chemistry, finance, and economics, with opportunities to discuss content and model responses in detail.

Qualifications

• Quantitative knowledge across math, physics, chemistry, finance and economics.
• Ability to review, annotate, and provide clear feedback on AI-generated content.
• Strong written and verbal communication for detailed explanations.

Responsibilities

• Review homework problems and AI responses across quantitative subjects.
• Explain reasoning, identify errors and misconceptions, and provide detailed feedback.
• Analyze and annotate materials for consistency and accuracy.
• Participate in written and verbal discussions about content and model responses.

Skills

Quantitative analysis

Problem-solving

Python proficiency

Finance concepts

Economics concepts

Education

Bachelor's degree in mathematics, science, engineering, economics, finance, or related field

Job description

Quant STEM Bachelor AI Training Reviewer (English)

Review homework problems and AI responses across quantitative subjects, then give clear feedback on accuracy and reasoning. This remote, part-time contractor role pays $20 to $45 per hour.

Remote Hourly · $20–$45/hr

$20–$45/hr

Contract, part-time

Remote

Open in 52 countries

• Algeria
• Argentina
• Austria
• Bahrain
• Bangladesh
• Belgium
• Brazil
• Canada
• Chile
• Colombia
• Denmark
• Egypt
• France
• Germany
• Ghana
• Greece
• India
• Indonesia
• Italy
• Japan
• Jordan
• Kazakhstan
• Kenya
• Kuwait
• Kyrgyzstan
• Lebanon
• Malaysia
• Mexico
• Morocco
• Netherlands
• Nigeria
• Oman
• Pakistan
• Palestine
• Peru
• Philippines
• Portugal
• Qatar
• Saudi Arabia
• Singapore
• South Africa
• Spain
• Sri Lanka
• Switzerland
• Taiwan
• Thailand
• Tunisia
• United Arab Emirates
• United Kingdom
• United States
• Uzbekistan
• Vietnam

The work

You will help improve AI systems by reviewing educational and quantitative content. The work covers school-level and introductory college problems, along with long-form model responses in several subjects.

You will explain your reasoning, identify errors and common misconceptions, and give detailed feedback on how well an AI system handles quantitative material.

• Analyze and annotate homework problems in mathematics, physics, chemistry, finance, and economics.
• Compare long-form responses for clarity, correctness, and educational value.
• Review and edit annotated materials for consistency and accuracy.
• Take part in detailed written and verbal discussions about the content and model responses.

What it pays and takes

This is a remote, part-time contractor role. Prior AI experience is not required, but quantitative subject knowledge is central to the work.

• Pay: $20 to $45 per hour.
• Work type: Remote contract work on a part-time basis.
• Location: Open to candidates in the countries listed for this role.
• Education: A bachelor's degree or equivalent experience in mathematics, science, engineering, economics, finance, or a related field.
• Skills: Strong quantitative analysis and problem-solving, Python proficiency, and familiarity with finance and economics concepts.
• Communication: Clear written and verbal communication, careful reading of complex multi-turn conversations, and strong attention to clarity and precision.
• Helpful background: Annotation, educational content review, or similar detailed feedback work.

About AI training work

AI training work is the human side of building artificial intelligence. Reviewers prepare examples and assess model responses so AI systems can handle real questions more accurately, and subject-matter knowledge helps produce useful, reliable feedback.

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