Key Facts

Remote From:

Part time

English

Hard Skills

Bayesian Statistics Applied Mathematics Python (Programming Language) Mathematical Software Linux Game Ai Simulation Software Benchmarking Evaluation Strategy Science Education +1 more

Other Skills

•
Strategic Thinking

Roles & Responsibilities

Graduate-level training in a relevant STEM field (MS, PhD, or equivalent research experience)
Proven proficiency with at least one scientific software library (PyMC, FEniCS, etc.)
Strong Python skills for writing problem setups and solution validators
Ability to work independently and refine problem designs

Requirements:

Design challenging computational problems to test AI capabilities in solving scientific and engineering tasks
Develop problems requiring the use of specialized scientific software for simulations and experiment design
Refine problems through iterative testing against state-of-the-art AI models to achieve target difficulty
Collaborate on creating tasks that require strategic thinking and efficient information extraction

Job description

About the job

Mercor connects elite creative and technical talent with leading AI research labs. Headquartered in San Francisco, our investors include Benchmark, General Catalyst, Peter Thiel, Adam D'Angelo, Larry Summers, and Jack Dorsey.

Position: Computational Bayesian Statistics and Applied Mathematics Expert
Type: Contract
Compensation: $70–$100/hour
Location: Remote
Commitment: 15–20 hours/week

Role Responsibilities

Design challenging computational problems to test AI capabilities in solving scientific and engineering tasks.
Develop problems requiring the use of specialized scientific software for simulations and experiment design.
Refine problems through iterative testing against state-of-the-art AI models to achieve target difficulty.
Collaborate on creating tasks that require strategic thinking and efficient information extraction.
Work independently to enhance problem designs based on feedback and model performance.

Qualifications

Must-Have

Graduate-level training in a relevant STEM field (MS, PhD, or equivalent research experience).
Proven proficiency with at least one scientific software library (PyMC, FEniCS, etc.).
Strong Python skills for writing problem setups and solution validators.
Ability to work independently and refine problem designs.
Comfortable in a Linux/terminal environment with remote compute sandboxes.
Available for at least 15–20 hours/week.

Preferred

Experience across multiple domains or tools.
Familiarity with benchmark or evaluation design.
Background in scientific teaching or exam/problem-set design.
Experience with computational reproducibility and containerized environments.

Application Process (Takes 20–30 mins to complete)

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AI interview based on your resume
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Resources & Support

For details about the interview process and platform information, please check: https://talent.docs.mercor.com/welcome
For any help or support, reach out to: support@mercor.com

PS: Our team reviews applications daily. Please complete your AI interview and application steps to be considered for this opportunity.

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