Remote AMO Physicist for AI Evaluation (PhD)

mercor; United States; Remote; USD 110,000 - 152,000; Part time

Job summary

Mercor is seeking an Atomic, Molecular and Optical Physicist (PhD) for a remote contract spanning 8 to 10 weeks, at 10 hours per week. The role focuses on evaluating AI-generated physics content, reviewing problems for principled accuracy, and providing structured feedback to improve model training and outputs.

Ideal candidates hold a PhD in the relevant field, have a publication record (3–5 papers), and are proficient in LaTeX, Python, SymPy, and Jupyter, with English at B2 level or higher.

Qualifications

• PhD in atomic, molecular or optical physics or closely related field.
• Published work on the specific phenomena mentioned.
• A verifiable publication record with three to five representative papers.
• Working proficiency with LaTeX, Python, SymPy, and Jupyter.
• English at B2 or above, including written reasoning.

Responsibilities

• Evaluate the accuracy and depth of AI-generated content in physics to strengthen reasoning and rigor in model outputs.
• Review complex physics problems for alignment with domain principles and methodologies.
• Provide clear, structured feedback to AI research teams to improve training data quality and downstream performance.
• Develop evaluation rubrics and benchmarks for assessing AI-generated physics tasks and solutions.
• Collaborate with subject matter experts to ensure consistency, relevance, and coverage across datasets.
• Work independently and asynchronously to meet deadlines while improving AI model performance.

Skills

English B2

LaTeX

Python

SymPy

Jupyter

Education

PhD in atomic, molecular or optical physics

Tools

LaTeX

Python

SymPy

Jupyter

Job description

Mercor is seeking an Atomic, Molecular and Optical Physicist (PhD) for a remote contract spanning 8 to 10 weeks, at 10 hours per week. The role focuses on evaluating AI-generated physics content, reviewing problems for principled accuracy, and providing structured feedback to improve model training and outputs.

Ideal candidates hold a PhD in the relevant field, have a publication record (3–5 papers), and are proficient in LaTeX, Python, SymPy, and Jupyter, with English at B2 level or higher.