Mathematics PhD - AI Evaluation Expert

Mercor; San Francisco (CA); On-site; USD 11,021,000 - 13,776,000; Full time

Job summary

Mercor is hiring PhD and Master's scientists to author AI evaluation tasks (Sci Code) for a new benchmark in scientific computing, partnering with leading AI labs. You will author original, executable research problems that frontier models cannot solve.

Engagement lasts 6 weeks, part-time with 20+ hours per week, start date immediate. Required: PhD in mathematics or related field, depth in two subdomains, Python for scientific computing, and experience with GitHub and Docker.

Qualifications

• PhD in mathematics, applied mathematics, computational mathematics, or a closely related field.
• Demonstrated depth in at least two of: numerical linear algebra, computational mechanics, computational finance.
• Working proficiency in Python for scientific computing.
• Comfortable with GitHub and running code in Docker — authoring runs through a pull-request workflow with automated quality checks.

Responsibilities

• Source your own material: a published paper, a Kaggle dataset, an open-source repository, or a scenario you design.
• Write scientific prompts based on the input.
• Build the grading criteria that define a correct answer.
• Calibrate against frontier models — a task ships only when strong models fail it more often than they succeed.

Skills

Python for scientific computing

Education

PhD in mathematics / applied mathematics / computational mathematics

Tools

GitHub

Docker

Job description

Mercor is hiring PhD and Master's scientists to author AI evaluation tasks (Sci Code)

Mercor is partnering with leading AI labs on a new benchmark for scientific computing. You will author original, executable research problems that today's frontier models cannot solve.

Domains - depth required in at least two subdomains (with a coding focus)

• Mathematics — numerical linear algebra, computational mechanics, computational finance

What you'll do

• Source your own material: a published paper, a Kaggle dataset, an open-source repository, or a scenario you design

• Write scientific prompts based on the input

• Build the grading criteria that define a correct answer

• Calibrate against frontier models — a task ships only when strong models fail it more often than they succeed

Required

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

• Demonstrated depth in at least two of the following subdomains: numerical linear algebra, computational mechanics, computational finance

• Working proficiency in Python for scientific computing

• Comfortable with Git/GitHub and running code in Docker — authoring runs through a pull-request workflow with automated quality checks

Preferred

• Publications in peer-reviewed journals

• Prior scientific software or research engineering experience

Engagement

• Duration: 6 weeks

• Commitment: part-time, 20+ hours per week

• Start date: immediate