Mathematics PhD - AI Evaluation Expert

Mercor; Greater London; On-site; GBP 69,000 - 124,000; Part time

Job summary

Mercor is hiring PhD and Master’s scientists to author AI evaluation tasks (Sci Code). You will author original, executable research problems that today’s frontier models cannot solve.

Engage with leading AI labs to build benchmarks for scientific computing and craft robust grading criteria. You will work on multiple subdomains with a coding focus, using Python or R, and Docker-based workflows. Start date is immediate for a 6-week, part-time engagement.

Qualifications

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

Git/GitHub

Docker

Numerical linear algebra

Computational mechanics

Computational finance

Education

PhD in Mathematics

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 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

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