Materials Scientist - Fully Remote | Upto $90/hr Part-time

mercor; Deutschland; A distancia; EUR 98.000 - 129.000; A tiempo parcial

Descripción de la vacante

Mercor is seeking a STEM QA Reviewer in Materials Engineering for a remote 3-week contract. The role focuses on evaluating prompts, verifying gold-standard solutions, and ensuring robust evaluation criteria to improve AI model training data.

The ideal candidate has an MS or PhD in Materials Science/Engineering and strong technical writing skills. You will independently select problems within your domain, render verdicts with clear explanations, and contribute to model performance improvements on

Formación

• Verify ground truth solutions for grad-level materials problems.
• Demonstrate strong scientific reasoning in evaluations.
• Communicate findings clearly in written form.

Responsabilidades

• Evaluate STEM problem prompts and verify golden answers for accuracy and clarity.
• Assess grading methodology and ensure robustness in evaluation criteria.
• Analyze and summarize model agent trajectories for best and worst rollouts.
• Provide structured feedback using standardized review forms to improve training data quality.
• Render Accept/Revise/Reject verdicts with detailed explanations to enhance AI model performance.
• Self-select problems within your domain expertise and work independently on the HFI (Surveyor) platform.

Conocimientos

Independent verification

Scientific reasoning

Written communication

Educación

MS or PhD in Materials Science/Engineering

Descripción del empleo

About the job

Mercor connects elite creative and technical talent with leading AI research labs. Headquartered in San Francisco, our investors include Benchmark , General Catalyst , Peter Thiel , Adam D'Angelo , Larry Summers , and Jack Dorsey . Position: STEM QA Reviewer - Materials Engineering Type: Contract Compensation: $90/hour Location: Remote Duration: 3-week engagement (6/5–6/25)

Role Responsibilities

• Evaluate STEM problem prompts and verify golden answers for accuracy and clarity.
• Assess grading methodology and ensure robustness in evaluation criteria.
• Analyze and summarize model agent trajectories for best and worst rollouts.
• Provide structured feedback using standardized review forms to improve training data quality.
• Render Accept/Revise/Reject verdicts with detailed explanations to enhance AI model performance.
• Self-select problems within your domain expertise and work independently on the HFI (Surveyor) platform.

Qualifications Must-Have

• MS or PhD in Materials Science / Materials Engineering or closely related field.
• Ability to independently verify ground truth solutions for grad-level materials problems.
• Strong scientific reasoning and written communication skills.
• ~2.5 reviews per week (~2-4 hours per review).

Resources & Support

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