Inorganic Materials AI Data Expert

About OpenTrain

OpenTrain AI is the hiring and contracting organization for this role. OpenTrain is the #1 platform for finding and building careers in AI training and data labeling, helping specialists discover projects, build a professional profile, and apply in minutes.

Creating an OpenTrain account is free, and your profile can help you grow a durable career in AI training through flexible, remote opportunities.

About AI Training Work

AI training is the human side of building advanced artificial intelligence. Expert contributors create, structure, review, and rate examples that help models learn how to reason accurately in specialized fields such as materials science and the physical sciences.

This work lets you apply professional knowledge to cutting-edge AI systems while working remotely and choosing a schedule that can fit around other commitments.

The Role

OpenTrain AI is seeking an Inorganic Materials, Semiconductor and Superconductor Expert to produce and evaluate scientific training data. You will apply deep knowledge of materials, devices, experimental methods, and characterization to help improve the technical quality of AI-generated scientific reasoning.

This is a remote, US-based contractor role paying $84 per hour. The engagement is long-term and ongoing, with work available for up to 40 hours per week. The listed time requirement is 20 or more hours per week, with a minimum engagement of 10 hours per week.

• Engagement: Contractor and part-time
• Location: Remote, US-based
• Pay: $84 per hour
• Duration: Long-term and ongoing
• Availability: 20 or more hours per week listed; minimum 10 hours per week

What You'll Do

You will generate, organize, and assess technical content used to train and evaluate AI models. The work requires careful scientific judgment, precise documentation, and the ability to explain why a response or procedure is technically sound.

• Apply expertise across synthesis, characterization, fabrication, and device physics.
• Create high-quality training and evaluation data for materials science and physical sciences.
• Review AI-generated scientific reasoning and identify technical errors.
• Design and solve challenging, expert-level problems in your specialization.
• Rate and rank model outputs against defined scientific criteria.
• Provide clear written reasoning for ratings and technical decisions.
• Convert experimental procedures, characterization results, and process data into organized, model-ready data.
• Deliver reliable, high-quality work within defined timelines.

Required Qualifications

This role is intended for someone with substantial hands-on expertise in inorganic materials, semiconductor, or superconductor research. You should be able to evaluate technical details and communicate your reasoning clearly in written English.

• Hands-on experimental experience in inorganic synthesis, including solid-state, solution, solvothermal, or sol-gel methods; superconducting materials; or semiconductors and advanced packaging.
• Strong materials or device characterization skills, including XRD, SEM, TEM, spectroscopy, or electrical and transport measurements.
• An advanced degree such as a PhD or MS, or equivalent hands-on experience, in materials science, chemistry, physics, or a related engineering field.
• Ability to evaluate AI-generated scientific reasoning for accuracy and technical detail.
• Clear written English and the ability to explain technical reasoning concisely.

Helpful Background

Experience with thin-film growth or device fabrication is valued. Familiarity with specialized processing and clean-room methods can help you contribute across a broader range of materials and device tasks.

• MBE or epitaxy
• MOCVD
• CVD
• Sputtering
• IBAD
• Etch processes
• Clean-room microfabrication

How to Apply Through OpenTrain

Create or update your free OpenTrain profile with your scientific background, relevant experimental experience, and availability. Then apply through OpenTrain to be considered for this remote AI training engagement.

By contributing your expertise, you can help shape how advanced AI models understand materials, devices, processes, and scientific reasoning.