Physics Research and AI Evaluation Specialist

About OpenTrain

OpenTrain is the #1 platform for people building careers in AI training and data labeling. Create a free profile, find specialized projects, and grow a durable freelance career doing the human work that trains modern AI.

We connect expert contributors directly to meaningful AI-training tasks and help you consolidate work, build a portfolio, and apply in minutes—while you collaborate remotely on cutting-edge projects.

The AI-training Industry In Brief

AI models learn from examples and human feedback: people annotate data, write and rate model outputs, and evaluate responses for accuracy and clarity. This work is remote-friendly, flexible, and a direct way to shape how state-of-the-art AI systems behave.

Physics experts are in demand to ensure scientific correctness and rigor in model outputs used for research, education, and technical assistance.

The Role

We are hiring a remote PhD Physicist to serve as a Physics Research and AI Evaluation Specialist. You will research fundamental and applied physics topics, analyze experimental results, craft clear instructional material, and evaluate AI-generated text for conceptual accuracy and scientific rigor.

This is a part-time contractor role requiring 20+ hours per week. Compensation is hourly, USD $70–$90/hr. Work is document-focused (research notes, explanations, written evaluations) and involves both rating and producing text as part of AI training workflows.

• Employment type: Contractor, Part-time
• Time commitment: 20+ hours/week
• Pay: $70–$90 USD per hour
• Data type: Documents; label types: Evaluation rating and text generation
• Language required: English; location: Worldwide (remote)

What You’ll Do Day-to-Day

• Investigate and summarize fundamental and applied physics topics and recent developments
• Analyze experimental data and interpret findings to support or critique physical models
• Write clear, concise explanations of complex scientific concepts for training materials
• Create and curate physics educational content used to teach and evaluate models
• Review AI-generated answers for accuracy, clarity, and scientific rigor and assign evaluation ratings
• Provide written and verbal feedback in iterative AI-training cycles and collaborate remotely with multidisciplinary teams

Requirements

• PhD in Physics or a closely related scientific field (required)
• Strong background in theoretical and experimental physics
• Proven experience conducting rigorous scientific research and publishing in peer-reviewed journals
• Ability to analyze experimental data and explain physical concepts clearly in writing
• Comfort evaluating AI-generated scientific content for accuracy and rigor
• Clear written and verbal communication skills for remote collaboration
• Experience teaching physics at the university or advanced undergraduate level is a plus

Who Should Apply

This role fits PhD-level physicists who want to apply their research skills to improve AI systems and educational content. You should enjoy translating complex ideas into clear explanations and assessing model outputs against scientific standards.

Although labeled Entry level for AI-training experience, the position requires advanced academic credentials and a track record of research, so it is ideal for scientists entering AI training from academia or research labs.

How It Works: Apply and Get Started

Create an OpenTrain account and complete your profile with your PhD and research background. Apply to this listing and, if selected, you will receive instructions for onboarding, sample tasks, and the tools needed to contribute.

Tasks are remote and document-based; you will rate AI responses, generate explanatory text when requested, and submit written evaluations. Contractors are paid hourly at the stated rate for approved work.

• Sign up on OpenTrain, complete your profile, and submit an application
• Selected contributors complete onboarding and sample validations before receiving paid tasks
• Work remotely and collaborate asynchronously with the OpenTrain team