Bayesian Statistics Expert - PhD - AI Trainer

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: STEM Computational Scientific Software & Evaluation Design - Computational Bayesian Statistics and Applied Mathematics
Type: Contract
Compensation: $70–$100/hour
Location: Remote
Commitment: 15–20 hours/week

Role Responsibilities

• Design graduate-level computational problems using domain-specific scientific software libraries such as PyMC, PyStan, FEniCS, and GUDHI.
• Develop problems that require strategic reasoning, including designing sequences of queries or experiments to uncover hidden information.
• Calibrate tasks against state-of-the-art AI models and refine problem designs to achieve target difficulty levels.
• Collaborate independently and asynchronously to iterate on problem designs based on calibration feedback.
• Utilize strong Python programming skills to write problem setups, oracle functions, and solution validators.
• Work comfortably in a Linux/terminal environment with remote compute sandboxes.

Qualifications

Must-Have

• Graduate-level training in a relevant STEM domain (MS, PhD, or equivalent research experience).
• Proficiency with at least one scientific software library such as PyMC, FEniCS, or GUDHI.
• Strong Python programming skills.
• Ability to work independently and iterate on problem designs.
• Comfortable in a Linux/terminal environment.

Preferred

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

Application Process (Takes 20–30 mins to complete)

• Upload resume
• AI interview based on your resume
• Submit form

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: [email protected]

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