Materials Science PhD - AI Evaluator - AI Trainer

mercor; United States; Remote; USD 80,000 - 113,000; Full time

Job summary

Mercor is seeking a Materials Science PhD Coding Expert for a six-week remote contract. The role demands deep knowledge of materials science and the ability to craft prompts to test AI models.

Responsibilities include sourcing data from papers and open sources, building grading criteria, and calibrating tasks against frontier models. Ideal candidates work independently, meet deadlines, and have strong Python or R skills, plus Git/GitHub and Docker familiarity.

Qualifications

• PhD in materials-related field.
• Proficient in Python or R for scientific computing.
• Experience with Git/GitHub and Docker.

Responsibilities

• Source material from papers, Kaggle datasets, open-source repos, or designed scenarios.
• Write scientific prompts based on input to challenge AI models.
• Build grading criteria to define correct answers for scientific tasks.
• Calibrate tasks against frontier models, shipping only when strong models fail more often.
• Work independently and asynchronously to meet deadlines and improve AI model performance.

Skills

Molecular modeling

Semiconductor materials

Python/R

Education

PhD in relevant field

Tools

Git/GitHub

Docker

Job description

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 .

Role Details

• Position: Material Science PhD Coding Experts
• Type: Contract
• Compensation: $70/hour
• Location: Remote
• Duration: 6 weeks
• Commitment: 20+ hours/week

Role Responsibilities

• Source material from published papers, Kaggle datasets, open-source repositories, or designed scenarios.
• Write scientific prompts based on sourced input to challenge AI models.
• Build grading criteria to define correct answers for scientific tasks.
• Calibrate tasks against frontier models, ensuring tasks ship only when strong models fail more often than succeed.
• Work independently and asynchronously to meet deadlines and improve AI model performance.

Qualifications

• Must-Have:
  • PhD in materials science, materials engineering, applied physics, chemistry, chemical engineering, or a closely related field.
  • Demonstrated depth in semiconductor materials and molecular modeling.
  • Working proficiency in Python , R , or another relevant programming language for scientific computing.
  • Comfortable with Git/GitHub and running code in Docker .
• Preferred:
  • Publications in peer-reviewed journals.
  • Prior scientific software or research engineering experience.

Start Date

Immediate

Interview Process

A 25-minute conversational interview covering your background, experience, and motivations.