Mathematics PhD Coding Experts

Weekday 1; United States; On-site; USD 83,000 - 110,000; Part time

Job summary

Weekday 1 is hiring PhD and Master's scientists to author AI evaluation tasks (Sci Code) for a new benchmark for scientific computing. You will author original, executable research problems that today's frontier models cannot solve.

You will source material, write scientific prompts, and build grading criteria. The role requires calibration against frontier models, with a 6-week, part-time commitment of 20+ hours per week and immediate start.

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 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

Git/GitHub

Docker

Education

PhD in mathematics, applied mathematics, or computational mathematics

Tools

Docker

GitHub

Job description

Compensation: $70 per hour

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

We are 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

Requirements

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

We consider all qualified applicants without regard to legally protected characteristics and provide reasonable accommodations upon request.