Computational Mathematician - Fully Remote | Upto $70/hr

mercor; United States; Remote; USD 83,000 - 124,000; Part time

Job summary

Mercor connects elite creative and technical talent with leading AI research labs. This remote contract role requires a PhD in mathematics and deep expertise in numerical methods, with Python proficiency and Docker/GitHub experience.

You will source datasets, craft prompts, define evaluation criteria, and calibrate tasks against frontier models, working independently to meet deadlines. The position runs for 6 weeks at ~20+ hours/week, with a contract-based compensation of $70/hour, and can be

Qualifications

• PhD in mathematics, applied mathematics, computational mathematics, or 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.

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.

Skills

Python

Independent work

Asynchronous work

Education

PhD in mathematics or closely related 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 .

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