Quantum Computing Research Engineer for AI Benchmarks

Obsidian; San Francisco (CA); On-site; USD 96,000 - 165,000; 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.

In this six-week, part-time role (20+ hours/week), you will source material, write prompts, build grading criteria, and calibrate against frontier models to ensure the tasks are challenging and robust. Start date is immediate, with a collaborative, research-oriented environment.

Qualifications

• PhD in physics, applied physics, or a closely related field.
• Demonstrated depth in at least two of: condensed matter, optics, quantum information/computing, computational physics, astrophysics, particle physics.
• Working proficiency in Python, R, or another relevant programming language for scientific computing.
• Comfortable with Git/GitHub and running code in Docker — authoring runs through a pull-request workflow with automated quality checks.
• Publications in peer-reviewed journals (preferred).
• Prior scientific software or research engineering experience (preferred).

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

Scientific computing

Education

PhD in physics

Tools

Docker

Git

Job description

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.

In this six-week, part-time role (20+ hours/week), you will source material, write prompts, build grading criteria, and calibrate against frontier models to ensure the tasks are challenging and robust. Start date is immediate, with a collaborative, research-oriented environment.