Physics Content Review Specialist

About OpenTrain AI

OpenTrain AI is the #1 platform for building careers in AI training and data labeling. We help people start and grow freelance careers teaching AI by centralizing projects, tracking work, and supporting professional development for contributors across the industry.

As the hiring and contracting organization for this role, OpenTrain AI connects subject-matter experts to projects that shape how state-of-the-art models understand and reason about the world.

About AI training work

AI training (also called data labeling or annotation) is the human side of building AI: people prepare, review, and improve the examples models learn from. Tasks range from annotating images and text to writing, rating, and editing model outputs.

This work is largely remote, often flexible and part-time, and gives contributors a direct role in how models behave. Projects frequently require domain knowledge — in this role, physics expertise is the core requirement.

The role

You will evaluate and annotate physics documents, review problem sets and research summaries, and provide expert feedback that helps models reason about scientific content. The position is remote, contractor, and part-time with a minimum commitment of 20+ hours per week.

Work will be performed asynchronously with project managers and other subject-matter experts to meet milestones and improve dataset quality.

• Employment type: Contractor, Part-time
• Time requirement: 20+ hours/week
• Work location: Remote, worldwide (asynchronous collaboration)
• Data type: Documents; label tasks include classification, text generation, and evaluation/rating

What you'll do

Your day-to-day work will center on reviewing and improving physics content used for AI training. Tasks combine critical evaluation, writing, and annotation.

• Evaluate scientific data, equations, and experimental findings across physics domains
• Create and review physics problem sets, research summaries, and technical explanations
• Provide detailed feedback on accuracy, clarity, and rigor of physics content for model training
• Author or edit analytical write-ups, experimental descriptions, and technical reports
• Identify gaps in data quality or coverage and recommend improvements for stronger model development
• Collaborate asynchronously with project managers and subject-matter experts to meet milestones

Requirements

Applicants must demonstrate formal physics training and practical experience producing technical writing or research output in physics.

• Degree: BSc, MSc, or PhD in Physics or a closely related discipline (required)
• Strong knowledge of classical mechanics, electromagnetism, thermodynamics, quantum mechanics, and modern physics
• Proven experience authoring or reviewing research papers, experimental reports, or technical write-ups in physics
• Experience with data analysis, experimental design, or computational modeling in physics
• Excellent English writing and communication skills with meticulous attention to detail
• Ability to simplify complex concepts for varied audiences and evaluate explanations for accuracy and clarity
• Comfort working remotely and collaborating asynchronously

Who should apply

This role suits physicists, postgraduates, researchers, or technical writers with a physics background who want to apply their expertise to AI training. It is labeled entry level in the project system but requires substantive domain knowledge and experience producing scientific documentation.

If you enjoy translating rigorous science into clear, testable content and want to influence how AI systems reason about physics, this project is a great fit.

Compensation and practical details

Pay is hourly, $20–$50 per hour (PAY_PER_HOUR). The listing requires English-language communication and is open to contributors worldwide. Tasks will be performed on document-based workflows and include classification, text generation, and evaluation/rating labeling types.

• Pay: $20–$50 USD per hour
• Label types: Classification, Text generation, Evaluation/rating
• Data type: Documents
• Languages: English
• Worldwide remote applicants accepted

How it works

Apply through OpenTrain AI to join the project. After selection you'll receive assignment details, guidelines, and examples for the specific physics workflows. Work is completed asynchronously against milestones and reviewed for quality; feedback helps you improve and grow on future projects.

OpenTrain provides a place to build a lasting portfolio of AI training work — contributing here can lead to more projects that leverage your physics expertise.