Materials Science Expert for AI Evaluation

About OpenTrain

OpenTrain AI is hiring expert contractors for cutting-edge AI training projects. OpenTrain is the #1 platform for finding and building careers in AI training and data labeling, helping people discover projects, create a profile, and apply in minutes.

This is a remote, part-time opportunity for a materials science or engineering expert to contribute specialized knowledge to the development of advanced AI systems.

• Contractor engagement
• Remote work worldwide
• Expected commitment of less than 20 hours per week
• Professional English required

About AI Training Work

AI training is the human side of building artificial intelligence. Experts review and improve model responses so AI systems can produce more accurate, technically sound, and useful results.

In this project, your materials science and engineering judgment will help evaluate technical answers, identify weaknesses in AI reasoning, and provide feedback that informs future model improvements.

• Work directly on the development of advanced AI capabilities
• Apply real-world technical judgment to model-generated content
• Help improve how AI reasons about specialized engineering problems
• Complete work remotely with flexible scheduling

The Role

As a Materials Science Expert, you will evaluate and solve advanced materials science and engineering problems spanning materials selection, failure analysis, testing, and process development. You will review AI-generated technical responses for correctness, accuracy, and overall engineering quality.

The work combines theoretical analysis with practical engineering judgment. You will assess real-world materials selection and failure scenarios, explain your reasoning clearly, and contribute domain expertise that helps refine AI performance in materials science and engineering.

• Role focus: Materials science and engineering AI evaluation
• Level: Expert
• Data formats and tasks include text evaluation, question answering, text generation, and RLHF
• Project duration is expected to be under one month
• Experts should be ready to begin shortly after onboarding

What You’ll Do

You will analyze technical content and provide precise feedback that meets project specifications. Strong written and verbal explanations are important because your evaluations will help communicate why an AI response is correct, incomplete, or technically flawed.

You will collaborate remotely with a distributed team of experts and project participants while documenting feedback consistently.

• Evaluate AI-generated materials science and engineering responses
• Assess technical correctness, accuracy, and engineering quality
• Solve advanced problems involving materials selection, failure analysis, testing, and process development
• Use microstructural analysis, fractography, mechanical testing, and thermodynamic or kinetic modeling
• Analyze tensile, fatigue, hardness, thermal, and related test data
• Apply root-cause analysis to materials failures and degradation mechanisms
• Document feedback and provide clear written and verbal explanations
• Contribute expertise that improves AI reasoning and model performance
• Collaborate with a distributed remote team

Requirements

This role is intended for an experienced materials professional with strong technical judgment and the ability to communicate complex engineering concepts in professional English.

• Bachelor’s degree or higher in Materials Science and Engineering, Metallurgy, or Mechanical Engineering or Chemical Engineering with a materials specialization
• At least three years of hands-on experience in materials selection, failure analysis, testing, or process development
• Expert knowledge of metals, polymers, ceramics, and composites
• Strong understanding of microstructure-property relationships and degradation or failure mechanisms
• Proven ability to analyze root-cause failures using fractography, metallography, and mechanical or thermal test data
• Familiarity with ASTM, ASM, or ISO materials standards and process qualification requirements
• Professional fluency in English with exceptional written and verbal communication skills
• Availability for less than 20 hours per week
• Ability to meet minimum weekly task submission requirements

Preferred Experience

Experience with materials characterization equipment or process development in a manufacturing environment is a plus. The project also strongly prefers evidence of rigor in authoring or evaluating challenging technical problems.

• Experience with SEM, XRD, TEM, DSC, or TGA
• Materials process development in a manufacturing environment
• Service on an olympiad problem committee
• Textbook problem-set or solutions-manual author credit
• Item-writing experience for an NCEES or academic qualifying-exam committee
• Service on an ASTM, ASM, or ISO materials standards committee
• Top placement or team leadership in the TMS Materials Bowl, ASM International undergraduate design competition, or an MRS student award
• Best-paper recognition at TMS Annual Meeting, MS&T, or MRS
• Publication in Acta Materialia or Nature Materials
• Acta Materialia Silver Medal, NSF CAREER, DOE Early Career, Sloan Fellowship, TMS Young Leader, or MRS Outstanding Young Investigator recognition

Compensation and Start Timeline

Compensation is output-based, with experts paid per task that meets project specifications. The time required for each task may vary according to experience and workflow, and minimum submission requirements apply. The listed compensation range is $80 to $130 USD per hour.

Roles are typically filled within 48 hours. If selected, you will be expected to start your first tasks within 24 to 48 hours after completing onboarding.

• Listed compensation range: $80-$130 USD per hour
• Output-based task compensation
• Minimum weekly task submissions required
• Expected project duration: under one month
• Start first tasks within 24-48 hours of onboarding

How to Apply

Create a free OpenTrain account and apply for this remote materials science AI evaluation opportunity. Highlight your materials expertise, relevant hands-on experience, technical communication skills, and any evidence of advanced problem-authoring or standards work.

• Apply through OpenTrain AI
• Showcase your education and materials engineering experience
• Mention relevant failure analysis, testing, characterization, or process development work
• Be prepared to complete onboarding before beginning project tasks