Materials Science AI Training Expert

About OpenTrain

OpenTrain is the #1 platform for finding and building careers in AI training and data labeling. OpenTrain AI hires and contracts specialists for projects that help shape how modern AI systems understand and communicate technical information.

Creating an OpenTrain account is free. You can build a professional AI training profile, show credible experience, discover projects aligned with your expertise, and apply in minutes.

About AI Training Work

AI training is the human side of building artificial intelligence. Specialists create examples, evaluate model responses, and provide detailed feedback so AI systems can produce more accurate, useful, and responsible answers.

In this role, your materials science judgment will help improve generative AI performance on technical questions involving engineering principles, scientific interpretation, calculations, and practical recommendations.

• Work remotely with flexible, part-time contractor hours
• Contribute to cutting-edge AI evaluation and human feedback projects
• Apply specialist knowledge to improve technical model behavior

The Role

OpenTrain AI is seeking a Materials Science AI Training Expert to support text-based AI evaluation and training. You will review AI-generated materials science content and create high-quality reference content that helps models produce accurate, practical, and clearly explained technical answers.

The work spans metals, ceramics, polymers, composites, phase diagrams, heat treatment, mechanical testing, corrosion, nanomaterials, and characterization. This contractor position is remote, requires 20 or more hours per week, and is available to candidates in Australia, Canada, Germany, New Zealand, the United Kingdom, and the United States.

Compensation is $60-$95 USD per hour, depending on the applicable project rate and work arrangement.

• Employment type: Part-time contractor
• Work arrangement: Remote
• Time requirement: 20+ hours per week
• Language: Professional English
• Eligible countries: Australia, Canada, Germany, New Zealand, United Kingdom, and United States
• Data type: Text
• Work types: Text generation, evaluation and rating, and RLHF

What You'll Do

You will assess whether AI-generated materials science answers are scientifically accurate, technically sound, and relevant to the prompt. Your feedback will help identify weaknesses and create dependable training examples for future model responses.

• Create prompts and gold-standard materials science answers
• Evaluate and rank AI-generated model outputs
• Provide precise written feedback using detailed guidelines
• Assess scientific accuracy, engineering reasoning, terminology, clarity, and physical plausibility
• Check unit consistency and microstructure-property relationships
• Review experimental interpretations and the relevance of responses to each prompt
• Identify hallucinated properties and unsupported performance claims
• Flag flawed processing recommendations, incorrect diagrams, unsafe design assumptions, and overconfident interpretations
• Fact-check technical claims and write accurate rewrites and model answers
• Maintain consistent quality across repeated review tasks

Required Qualifications

Candidates should have a bachelor's degree or higher in materials science, materials engineering, mechanical engineering, chemical engineering, metallurgy, polymer science, nanotechnology, or a related field. Equivalent professional experience may also qualify.

At least three years of relevant experience in research, engineering, laboratory work, manufacturing, teaching, technical writing, academic review, or related scientific or engineering work is required. The role is listed at an entry level, but applicants must still meet this technical experience requirement.

• Deep knowledge of crystal structures, phase diagrams, mechanical behavior, heat treatment, polymers, ceramics, metals, composites, corrosion, and characterization techniques
• Ability to evaluate structure-property reasoning, calculations, diagrams, experimental interpretations, and engineering recommendations
• Ability to diagnose issues involving phase transformations, polymer behavior, ceramic flaws, composites, and microstructure
• Skill in detecting hallucinated properties, flawed processing claims, unsafe engineering suggestions, and unsupported performance claims
• Strong professional English and precise technical communication
• Careful attention to detail and sound technical judgment
• Ability to apply detailed guidelines consistently
• Reliable, self-directed collaboration across time zones

Preferred Experience and Working Style

Experience with AI training, scientific quality assurance, engineering quality assurance, technical content review, or rubric-based evaluation is preferred. The strongest candidates will be comfortable translating advanced materials science knowledge into clear written explanations and consistent quality judgments.

• Materials science research or engineering experience
• Laboratory, manufacturing, or characterization experience
• Teaching, technical writing, or academic review experience
• Prior work evaluating scientific or engineering content
• Experience with AI training or human feedback workflows

How to Apply Through OpenTrain

Create a free OpenTrain account and build a profile that highlights your materials science education, professional experience, and technical communication strengths. A focused profile helps you present credible proof of work and find AI training opportunities aligned with your expertise.

Apply through OpenTrain to be considered for this remote materials science AI evaluation contract.