Mathematics PhD - AI Evaluation Expert

Mercor; Mumbai; On-site; INR 1,339,000 - 2,009,000; Part time

Job summary

Mercor is seeking PhD and Master’s scientists to author AI evaluation tasks for a new benchmark in scientific computing. You will author original, executable research problems that frontier models cannot solve, with a focus on two or more deep subdomains and a coding emphasis.

You will source material, write scientific prompts, and build robust grading criteria while calibrating against models that fail. Engagement spans six weeks, part-time with 20+ hours weekly, and an immediate start date.

Qualifications

• PhD in mathematics or related field.
• Depth in at least two of: numerical linear algebra, computational mechanics, computational finance.
• Proficiency in Python or R for scientific computing.
• Familiar with Git/GitHub and Docker; PR-based workflow with automated checks.

Responsibilities

• Source materials: papers, datasets, or scenarios you design.
• Write scientific prompts based on inputs.
• Build grading criteria for correct answers.
• Calibrate against frontier models; a task ships only when strong models fail it more often than it succeeds.

Skills

Numerical linear algebra

Computational mechanics

Computational finance

Education

PhD in mathematics

Tools

Python

R

Git/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 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

Process

1. A 25-minute conversational interview covering your background, experience, and motivations

2. Follow up within a few days with next steps and onboarding