Mathematics PhD - AI Evaluation Expert

mercor; Deutschland; Remote; EUR 74,000 - 98,000; Full time

Job summary

Mercor seeks a Mathematics PhD Coding Expert for a 6-week remote contract. The position pays $70/hour and requires 20+ hours per week with immediate start. You will source materials, craft prompts, and set grading criteria to evaluate frontier models, working autonomously to meet deadlines and improve AI performance.

Applicants should hold a PhD in mathematics or related field, show depth in at least two subdomains, and be proficient in Python. Familiarity with GitHub and Docker is expected.

Qualifications

• PhD in mathematics or closely related field.
• Depth in at least two subdomains: numerical linear algebra, computational mechanics, or computational finance.
• Proficiency in Python for scientific computing and data processing.
• Experience with Git/GitHub and running code in Docker environments.

Responsibilities

• Source material from papers, Kaggle datasets, open sources, or self-designed scenarios.
• Write scientific prompts based on sourced inputs.
• Build grading criteria to define correct answers.
• Calibrate tasks against frontier models to ensure failure-driven improvements.
• Work independently and asynchronously to meet deadlines while improving AI model performance.

Skills

Python for scientific computing

Git/GitHub experience

Docker usage

Education

PhD in mathematics, applied mathematics, computational mathematics, or closely related field

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 .

Position: Mathematics 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 self-designed scenarios.
• Write scientific prompts based on sourced inputs.
• Build grading criteria to define correct answers.
• Calibrate tasks against frontier models, ensuring tasks ship only when strong models fail more often than succeed.
• Work independently and asynchronously to meet deadlines while improving AI model performance .

Qualifications Must-Have

• PhD in mathematics, applied mathematics, computational mathematics, or a closely related field.
• Depth in at least two subdomains: numerical linear algebra, computational mechanics, computational finance.
• Working proficiency in Python 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.
• Follow up within a few days with next steps and onboarding.

Resources & Support

• For details about the interview process and platform information, please check:
• For any help or support, reach out to:

Originally posted on Himalayas