AI Benchmark Scientist — Computational Mathematics

Mercor; Greater London; Hybrid; GBP 55,000 - 96,000; Part time

Job summary

Mercor is seeking PhD and Master’s scientists to author AI evaluation tasks (Sci Code) for a 6-week, part-time engagement in London. You will design original, executable research problems for frontier models and calibrate scoring against model failures.

Responsibilities include sourcing materials, writing prompts, building grading criteria, and testing runs in a pull-request workflow with Docker/Git. Start date is immediate; ~20+ hours per week with flexible scheduling and remote-friendly setup

Qualifications

• PhD in mathematics, applied mathematics, computational mathematics, or closely related field.
• Depth in at least two of: numerical linear algebra, computational mechanics, computational finance.
• Working proficiency in Python or R for scientific computing.
• Comfortable with Git/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

R

Education

PhD in Mathematics

Master's in Mathematics or related field

Tools

Git/GitHub

Docker

Job description

Mercor is seeking PhD and Master’s scientists to author AI evaluation tasks (Sci Code) for a 6-week, part-time engagement in London. You will design original, executable research problems for frontier models and calibrate scoring against model failures.

Responsibilities include sourcing materials, writing prompts, building grading criteria, and testing runs in a pull-request workflow with Docker/Git. Start date is immediate; ~20+ hours per week with flexible scheduling and remote-friendly setup