Key Facts

Remote From:

Part time

English

Hard Skills

Python (Programming Language) LTspice Linux Performance Improvement Benchmarking Evaluation Strategy Science Education Containerization

Other Skills

•
Collaboration

Roles & Responsibilities

Graduate-level training in a relevant STEM domain (MS, PhD, or equivalent research experience)
Demonstrated proficiency with scientific software libraries like scikit-rf or ngspice
Strong Python programming skills for writing problem setups and solution validators
Ability to work in a Linux/terminal environment with remote compute sandboxes

Requirements:

Design graduate-level computational problems using domain-specific scientific software libraries
Develop problems requiring sophisticated use of scikit-rf for RF and microwave network analysis and ngspice for circuit simulation
Calibrate tasks against state-of-the-art AI models and refine designs to achieve target difficulty
Create problems that demand strategic reasoning to uncover hidden information from data

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: STEM Computational Scientific Software & Evaluation Design - Electrical Engineering & RF/Circuit Design
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.
Develop problems requiring sophisticated use of scikit-rf for RF and microwave network analysis and ngspice for circuit simulation.
Calibrate tasks against state-of-the-art AI models and refine designs to achieve target difficulty.
Create problems that demand strategic reasoning to uncover hidden information from data.
Work independently and iterate on problem designs based on calibration feedback.
Collaborate asynchronously with teams to improve AI model performance.

Qualifications

Must-Have

Graduate-level training in a relevant STEM domain (MS, PhD, or equivalent research experience).
Demonstrated proficiency with scientific software libraries like scikit-rf or ngspice.
Strong Python programming skills for writing problem setups and solution validators.
Ability to work in a Linux/terminal environment with remote compute sandboxes.
Available for at least 15–20 hours per week.

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)

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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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